Assignment3
Eduardo Ramirez"
3/04/2020
Problem 10
This question should be answered using the Weekly data set, which is part of the ISLR package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1, 089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010
(a) Produce some numerical and graphical summaries of the Weekly data. Do there appear to be any patterns?
#install.packages('ISLR')
library(ISLR)## Warning: package 'ISLR' was built under R version 3.6.3summary(Weekly)## Year Lag1 Lag2 Lag3
## Min. :1990 Min. :-18.1950 Min. :-18.1950 Min. :-18.1950
## 1st Qu.:1995 1st Qu.: -1.1540 1st Qu.: -1.1540 1st Qu.: -1.1580
## Median :2000 Median : 0.2410 Median : 0.2410 Median : 0.2410
## Mean :2000 Mean : 0.1506 Mean : 0.1511 Mean : 0.1472
## 3rd Qu.:2005 3rd Qu.: 1.4050 3rd Qu.: 1.4090 3rd Qu.: 1.4090
## Max. :2010 Max. : 12.0260 Max. : 12.0260 Max. : 12.0260
## Lag4 Lag5 Volume
## Min. :-18.1950 Min. :-18.1950 Min. :0.08747
## 1st Qu.: -1.1580 1st Qu.: -1.1660 1st Qu.:0.33202
## Median : 0.2380 Median : 0.2340 Median :1.00268
## Mean : 0.1458 Mean : 0.1399 Mean :1.57462
## 3rd Qu.: 1.4090 3rd Qu.: 1.4050 3rd Qu.:2.05373
## Max. : 12.0260 Max. : 12.0260 Max. :9.32821
## Today Direction
## Min. :-18.1950 Down:484
## 1st Qu.: -1.1540 Up :605
## Median : 0.2410
## Mean : 0.1499
## 3rd Qu.: 1.4050
## Max. : 12.0260Volume and year seem to be related
(b) Use the full data set to perform a logistic regression with Direction as the response and the five lag variables plus Volume as predictors. Use the summary function to print the results. Do any of the predictors appear to be statistically significant? If so, which ones?
attach(Weekly)
glm.fit = glm(Direction ~ Lag1 + Lag2 + Lag3 + Lag4 + Lag5 + Volume, data = Weekly, family = binomial)
summary(glm.fit)##
## Call:
## glm(formula = Direction ~ Lag1 + Lag2 + Lag3 + Lag4 + Lag5 +
## Volume, family = binomial, data = Weekly)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6949 -1.2565 0.9913 1.0849 1.4579
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.26686 0.08593 3.106 0.0019 **
## Lag1 -0.04127 0.02641 -1.563 0.1181
## Lag2 0.05844 0.02686 2.175 0.0296 *
## Lag3 -0.01606 0.02666 -0.602 0.5469
## Lag4 -0.02779 0.02646 -1.050 0.2937
## Lag5 -0.01447 0.02638 -0.549 0.5833
## Volume -0.02274 0.03690 -0.616 0.5377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1496.2 on 1088 degrees of freedom
## Residual deviance: 1486.4 on 1082 degrees of freedom
## AIC: 1500.4
##
## Number of Fisher Scoring iterations: 4Lag2
(c) Compute the confusion matrix and overall fraction of correct predictions. Explain what the confusion matrix is telling you about the types of mistakes made by logistic regression.
glm.probs = predict(glm.fit, type = "response")
glm.pred = rep("Down", length(glm.probs))
glm.pred[glm.probs > 0.5] = "Up"
table(glm.pred, Direction)## Direction
## glm.pred Down Up
## Down 54 48
## Up 430 557When prediction is “Down”, model is right 54/(54+48)=52.9%. When prediction is “Up”, model is right 557/(430+557)=56.4% Model is has higher accuracy when the prediction is “Up”
(d) Now fit the logistic regression model using a training data period from 1990 to 2008, with Lag2 as the only predictor. Compute the confusion matrix and the overall fraction of correct predictions for the held out data (that is, the data from 2009 and 2010).
train.yrs <- Weekly$Year %in% (1990:2008)
train <- Weekly[train.yrs,]
test <- Weekly[!train.yrs,]
fit2 <- glm(Direction~Lag2, data=train, family=binomial)
fit2.prob <- predict(fit2, test, type="response")
fit2.pred <- ifelse(fit2.prob > 0.5, "Up", "Down")
table(fit2.pred, test$Direction)##
## fit2.pred Down Up
## Down 9 5
## Up 34 56mean(fit2.pred == test$Direction) ## [1] 0.625(e) Repeat (d) using LDA.
library(MASS)
fit.lda <- lda(Direction~Lag2, data=train)
fit.lda.pred <- predict(fit.lda, test)$class
table(fit.lda.pred, test$Direction)##
## fit.lda.pred Down Up
## Down 9 5
## Up 34 56mean(fit.lda.pred == test$Direction)## [1] 0.625(f) Repeat (d) using QDA.
fit.qda <- qda(Direction~Lag2, data=train)
fit.qda.pred <- predict(fit.qda, test)$class
table(fit.qda.pred, test$Direction)##
## fit.qda.pred Down Up
## Down 0 0
## Up 43 61mean(fit.qda.pred == test$Direction)## [1] 0.5865385(g) Repeat (d) using KNN with K = 1.
library(class)
set.seed(1)
train.X <- as.matrix(train$Lag2)
test.X <- as.matrix(test$Lag2)
knn.pred <- knn(train.X, test.X, train$Direction, k=1)
table(knn.pred, test$Direction)##
## knn.pred Down Up
## Down 21 30
## Up 22 31mean(knn.pred == test$Direction) ## [1] 0.5(h) Which of these methods appears to provide the best results on this data?
LDA and LOgistic regression have the best accueracy
(i) Experiment with different combinations of predictors, including possible transformations and interactions, for each of the methods. Report the variables, method, and associated confusion matrix that appears to provide the best results on the held out data. Note that you should also experiment with values for K in the KNN classifier.
##Problem 11
(a) Create a binary variable, mpg01, that contains a 1 if mpg contains a value above its median, and a 0 if mpg contains a value below its median. You can compute the median using the median() function. Note you may find it helpful to use the data.frame() function to create a single data se containing both mpg01 and the other Auto variables. 172 4. Classification
(b) Explore the data graphically in order to investigate the association between mpg01 and the other features. Which of the other features seem most likely to be useful in predicting mpg01? Scatterplots and boxplots may be useful tools to answer this question. Describe your findings.
pairs(Auto)
cor(Auto[, -9])## mpg cylinders displacement horsepower weight
## mpg 1.0000000 -0.7776175 -0.8051269 -0.7784268 -0.8322442
## cylinders -0.7776175 1.0000000 0.9508233 0.8429834 0.8975273
## displacement -0.8051269 0.9508233 1.0000000 0.8972570 0.9329944
## horsepower -0.7784268 0.8429834 0.8972570 1.0000000 0.8645377
## weight -0.8322442 0.8975273 0.9329944 0.8645377 1.0000000
## acceleration 0.4233285 -0.5046834 -0.5438005 -0.6891955 -0.4168392
## year 0.5805410 -0.3456474 -0.3698552 -0.4163615 -0.3091199
## origin 0.5652088 -0.5689316 -0.6145351 -0.4551715 -0.5850054
## acceleration year origin
## mpg 0.4233285 0.5805410 0.5652088
## cylinders -0.5046834 -0.3456474 -0.5689316
## displacement -0.5438005 -0.3698552 -0.6145351
## horsepower -0.6891955 -0.4163615 -0.4551715
## weight -0.4168392 -0.3091199 -0.5850054
## acceleration 1.0000000 0.2903161 0.2127458
## year 0.2903161 1.0000000 0.1815277
## origin 0.2127458 0.1815277 1.0000000MPG inversly corrilated with cylinders, wght, and hp.
(c) Split the data into a training set and a test set.
trainid <- sample(1:nrow(Auto), nrow(Auto)*0.7 , replace=F)
train <- Auto[trainid,]
test <- Auto[-trainid,]12.6% error
(e) Perform QDA on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?
#qda.fit = qda(mpg ~ cylinders + weight + displacement + horsepower, data = Auto, subset = train)
#qda.pred = predict(qda.fit, Auto.test)
#mean(qda.pred$class != mpg.test)11% error
(f) Perform logistic regression on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?
#fit.logit <- glm(mpg01~displacement+horsepower+weight+acceleration, data=train, family=binomial)
#logit.prob <- predict(fit.logit, test, type="response")
#logit.pred <- ifelse(logit.prob > 0.5, 1, 0)
#table(logit.pred, test$mpg01)
#mean(logit.pred != test$mpg01)error 12.7
(g) Perform KNN on the training data, with several values of K, in order to predict mpg01. Use only the variables that seemed most associated with mpg01 in (b). What test errors do you obtain? Which value of K seems to perform the best on this data set?
train.X <- cbind(train$displacement, train$horsepower, train$weight, train$acceleration)
test.X <- cbind(test$displacement, test$horsepower, test$weight, test$acceleration)
knn.pred <- knn(train.X, test.X, train$mpg, k=1)
table(knn.pred, test$mpg)##
## knn.pred 11 12 13 14 15 15.5 16 16.2 16.5 17 17.5 18 18.5 18.6 19 19.2 20
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 1 1 3 1 1 0 0 0 0 0 0 0 0 0 0
## 14 0 0 3 1 1 0 1 0 0 1 1 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0
## 16.5 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 20.2 20.6 21 21.1 21.6 22 22.3 23 23.2 23.9 24 24.2 25 25.1 25.5
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## 19.9 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 20 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0
## 21.5 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 27 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
##
## knn.pred 26 26.5 26.8 27 28 28.8 29 29.5 29.8 29.9 30 30.9 31 31.5 32 32.1
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## 25.8 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 28 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## 28.4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 32.4 33 34 34.1 35 35.1 36 36.1 37 39.1 40.8 41.5 43.4
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 1 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 1 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 1 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 2 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 1 0 0 0 0 0 0 0 0 0
## 30.5 0 1 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 1 1 0 0 0 1 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 1
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 1 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 1 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 1 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 1 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 1 0 0mean(knn.pred != test$mpg)## [1] 0.9322034knn.pred <- knn(train.X, test.X, train$mpg, k=10)
table(knn.pred, test$mpg)##
## knn.pred 11 12 13 14 15 15.5 16 16.2 16.5 17 17.5 18 18.5 18.6 19 19.2 20
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 1 2 3 6 4 1 2 0 2 0 0 1 0 0 0 0 0
## 14 0 0 2 0 1 1 1 0 0 1 1 0 1 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 20.2 20.6 21 21.1 21.6 22 22.3 23 23.2 23.9 24 24.2 25 25.1 25.5
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## 20.5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## 22 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 1 1 0 1 0 0 1 1 0 0 3 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 1 0 0 1 0 2 0 0
## 26.4 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 26 26.5 26.8 27 28 28.8 29 29.5 29.8 29.9 30 30.9 31 31.5 32 32.1
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 1 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 32.4 33 34 34.1 35 35.1 36 36.1 37 39.1 40.8 41.5 43.4
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 1
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 1 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 1 0 0 1 0 0 0 1 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 1 0 1 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 1 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 0 0 0 0 1 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 1 1 0 0 0 1 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 1 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 1 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 1 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 1 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0mean(knn.pred != test$mpg)## [1] 0.9067797knn.pred <- knn(train.X, test.X, train$mpg, k=100)
table(knn.pred, test$mpg)##
## knn.pred 11 12 13 14 15 15.5 16 16.2 16.5 17 17.5 18 18.5 18.6 19 19.2 20
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 1 2 5 6 2 1 3 0 1 0 1 0 0 0 0 0 0
## 14 0 0 1 0 4 1 0 0 1 2 0 1 1 1 1 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 1 0 1 1 0 1 0 1 0 0 5 1 1
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 20.2 20.6 21 21.1 21.6 22 22.3 23 23.2 23.9 24 24.2 25 25.1 25.5
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 1 1 0 0 1 4 1 1 1 0 1 1 2 1 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 1 0 0 0 0 2 0 0 0 0 1 0 1
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 0 0 0 0 0 0 1 0 0 2 0 3 0 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 26 26.5 26.8 27 28 28.8 29 29.5 29.8 29.9 30 30.9 31 31.5 32 32.1
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 2 0 0 1 0 0 2 1 1 0 1 1 1 1 0 1
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## knn.pred 32.4 33 34 34.1 35 35.1 36 36.1 37 39.1 40.8 41.5 43.4
## 9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0 0
## 12 0 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15 0 0 0 0 0 0 0 0 0 0 0 0 0
## 15.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 16.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 17.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 18.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 19.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 20.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21 0 0 0 0 0 0 0 0 0 0 0 0 0
## 21.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 22.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 23.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 24.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 25.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26 0 2 1 1 1 1 1 1 0 1 1 1 0
## 26.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 26.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 27.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28 1 0 1 0 1 0 0 0 1 0 0 0 1
## 28.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 28.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29 0 0 0 0 0 0 0 0 0 0 0 0 0
## 29.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 30.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 31.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 32.9 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 33.8 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 34.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 35.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 36.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 37.7 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0 0 0 0
## 38.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39 0 0 0 0 0 0 0 0 0 0 0 0 0
## 39.4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 43.1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 44.6 0 0 0 0 0 0 0 0 0 0 0 0 0
## 46.6 0 0 0 0 0 0 0 0 0 0 0 0 0mean(knn.pred != test$mpg)## [1] 0.9322034knn best at 10
##Problem 13
Using the Boston data set, fit classification models in order to predict whether a given suburb has a crime rate above or below the median. Explore logistic regression, LDA, and KNN models using various subsets of the predictors. Describe your findings.
data(Boston)
summary(Boston)## crim zn indus chas
## Min. : 0.00632 Min. : 0.00 Min. : 0.46 Min. :0.00000
## 1st Qu.: 0.08204 1st Qu.: 0.00 1st Qu.: 5.19 1st Qu.:0.00000
## Median : 0.25651 Median : 0.00 Median : 9.69 Median :0.00000
## Mean : 3.61352 Mean : 11.36 Mean :11.14 Mean :0.06917
## 3rd Qu.: 3.67708 3rd Qu.: 12.50 3rd Qu.:18.10 3rd Qu.:0.00000
## Max. :88.97620 Max. :100.00 Max. :27.74 Max. :1.00000
## nox rm age dis
## Min. :0.3850 Min. :3.561 Min. : 2.90 Min. : 1.130
## 1st Qu.:0.4490 1st Qu.:5.886 1st Qu.: 45.02 1st Qu.: 2.100
## Median :0.5380 Median :6.208 Median : 77.50 Median : 3.207
## Mean :0.5547 Mean :6.285 Mean : 68.57 Mean : 3.795
## 3rd Qu.:0.6240 3rd Qu.:6.623 3rd Qu.: 94.08 3rd Qu.: 5.188
## Max. :0.8710 Max. :8.780 Max. :100.00 Max. :12.127
## rad tax ptratio black
## Min. : 1.000 Min. :187.0 Min. :12.60 Min. : 0.32
## 1st Qu.: 4.000 1st Qu.:279.0 1st Qu.:17.40 1st Qu.:375.38
## Median : 5.000 Median :330.0 Median :19.05 Median :391.44
## Mean : 9.549 Mean :408.2 Mean :18.46 Mean :356.67
## 3rd Qu.:24.000 3rd Qu.:666.0 3rd Qu.:20.20 3rd Qu.:396.23
## Max. :24.000 Max. :711.0 Max. :22.00 Max. :396.90
## lstat medv
## Min. : 1.73 Min. : 5.00
## 1st Qu.: 6.95 1st Qu.:17.02
## Median :11.36 Median :21.20
## Mean :12.65 Mean :22.53
## 3rd Qu.:16.95 3rd Qu.:25.00
## Max. :37.97 Max. :50.00crim01 <- ifelse(Boston$crim > median(Boston$crim), 1, 0)
mydf <- data.frame(Boston, crim01)
pairs(mydf) # pred1 = age, dis, lstat, medv
sort(cor(mydf)[1,]) # pred2 = tax, rad (highest correlations with crim)## medv black dis rm zn chas
## -0.38830461 -0.38506394 -0.37967009 -0.21924670 -0.20046922 -0.05589158
## ptratio age indus crim01 nox lstat
## 0.28994558 0.35273425 0.40658341 0.40939545 0.42097171 0.45562148
## tax rad crim
## 0.58276431 0.62550515 1.00000000trainid <- sample(1:nrow(mydf), nrow(mydf)*0.7 , replace=F) # 70% train, 30% test
train <- mydf[trainid,]
test <- mydf[-trainid,]
train.X1 <- cbind(train$age, train$dis, train$lstat, train$medv)
test.X1 <- cbind(test$age, test$dis, test$lstat, test$medv)
train.X2 <- cbind(train$tax, train$rad)
test.X2 <- cbind(test$tax, test$rad)
# Logistic Regression models
fit.logit1 <- glm(crim01~age+dis+lstat+medv, data=train, family=binomial)
logit1.prob <- predict(fit.logit1, test, type="response")
logit1.pred <- ifelse(logit1.prob > 0.5, 1, 0)
mean(logit1.pred != test$crim01) # error rate## [1] 0.1973684fit.logit2 <- glm(crim01~tax+rad, data=train, family=binomial)
logit2.prob <- predict(fit.logit2, test, type="response")
logit2.pred <- ifelse(logit2.prob > 0.5, 1, 0)
mean(logit2.pred != test$crim01) # error rate## [1] 0.2368421# LDA models
fit.lda1 <- lda(crim01~age+dis+lstat+medv, data=train)
fit.lda1.pred <- predict(fit.lda1, test)$class
mean(fit.lda1.pred != test$crim01) # error rate## [1] 0.2171053fit.lda2 <- lda(crim01~tax+rad, data=train)
fit.lda2.pred <- predict(fit.lda2, test)$class
mean(fit.lda2.pred != test$crim01) # error rate## [1] 0.2763158# QDA models
fit.qda1 <- qda(crim01~age+dis+lstat+medv, data=train)
fit.qda1.pred <- predict(fit.qda1, test)$class
mean(fit.qda1.pred != test$crim01) # error rate## [1] 0.2697368fit.qda2 <- qda(crim01~tax+rad, data=train)
fit.qda2.pred <- predict(fit.qda2, test)$class
mean(fit.qda2.pred != test$crim01) # error rate## [1] 0.2236842# KNN models
knn1.pred <- knn(train.X1, test.X1, train$crim01, k=1)
mean(knn1.pred != test$crim01)## [1] 0.2631579knn1.pred <- knn(train.X1, test.X1, train$crim01, k=5)
mean(knn1.pred != test$crim01)## [1] 0.2565789knn1.pred <- knn(train.X1, test.X1, train$crim01, k=10)
mean(knn1.pred != test$crim01)## [1] 0.2302632