A3-MultiLogisticRegression
Rishabh Sabarwal
27 July 2017
Problem Definition
Here, we have a dataset, containing diagnostic measurements of more than 700 females.
Now, based on these data variables available, we need to predict wether the female is a Diabetic or not.
Variable Description
Pregnancies: Number of times pregnant
Glucose: Plasma glucose concentration a 2 hours in an oral glucose tolerance test
BloodPressure: Diastolic blood pressure (mm Hg)
SkinThickness: Triceps skin fold thickness (mm)
Insulin: 2-Hour serum insulin (mu U/ml)
BMI: Body mass index (weight in kg/(height in m)^2)
DiabetesPedigreeFunction: Diabetes pedigree function
Age: Age (years)
Outcome: Shows wether the person has Diabetes (1) or Not (0)
Setup
Loading Libraries
library(tidyr)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2)
library(corrgram)
library(gridExtra)##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
##
## combinelibrary(caret)## Loading required package: latticelibrary(pscl)## Loading required package: MASS##
## Attaching package: 'MASS'## The following object is masked from 'package:dplyr':
##
## select## Classes and Methods for R developed in the## Political Science Computational Laboratory## Department of Political Science## Stanford University## Simon Jackman## hurdle and zeroinfl functions by Achim Zeileislibrary(data.table)##
## Attaching package: 'data.table'## The following objects are masked from 'package:dplyr':
##
## between, first, lastlibrary(zoo)##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numericFunctions
Dataset
dfrModel <- read.csv("C:/firstproject/train-diabetes.csv", header=T, stringsAsFactors=F)
head(dfrModel)## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## DiabetesPedigreeFunction Age Outcome
## 1 0.627 50 1
## 2 0.351 31 0
## 3 0.672 32 1
## 4 0.167 21 0
## 5 2.288 33 1
## 6 0.201 30 0Observation
The dataset consists of all numeric data.
Missing Data
#sum(is.na(dfrModel$Age))
lapply(dfrModel, FUN=detect_na)## $Pregnancies
## [1] 0
##
## $Glucose
## [1] 0
##
## $BloodPressure
## [1] 0
##
## $SkinThickness
## [1] 0
##
## $Insulin
## [1] 0
##
## $BMI
## [1] 0
##
## $DiabetesPedigreeFunction
## [1] 0
##
## $Age
## [1] 0
##
## $Outcome
## [1] 0Observation
No columns with missing data found
Now, the data consists of 0 value in many columns.
This 0 Value is not acceptable for drawing any inferences of any calculation.
E.g. A 0 insulin level or 0 blood pressure logically does not refer to a healthy (or a living) person
It may be the case that the respective data was not available , and was substituted 0.
But, In this case, we choose to retain 0, seeing it as a value itself.
Detecting Outliers
#detect_outliers(dfrModel$Age)
lapply(dfrModel, FUN=detect_outliers)## $Pregnancies
## integer(0)
##
## $Glucose
## integer(0)
##
## $BloodPressure
## [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## $SkinThickness
## integer(0)
##
## $Insulin
## [1] 543 846 495 485 495 478 744 680 545 465 579 474 480 600 540 480
##
## $BMI
## [1] 0.0 0.0 0.0 0.0 0.0 67.1 0.0 0.0 0.0 0.0 0.0
##
## $DiabetesPedigreeFunction
## [1] 2.288 1.893 1.781 2.329 2.137 1.731 2.420 1.699 1.698
##
## $Age
## [1] 81
##
## $Outcome
## integer(0)Outliers Graph
plotgraph <- function(inp, na.rm=TRUE) {
outplot <- ggplot(dfrModel, aes(x="", y=inp)) +
geom_boxplot(aes(fill=inp), color="blue") +
labs(title="Diabetes Outcome Outliers")
outplot
}lapply(dfrModel, FUN=plotgraph)## $Pregnancies
##
## $Glucose
##
## $BloodPressure
##
## $SkinThickness
##
## $Insulin
##
## $BMI
##
## $DiabetesPedigreeFunction
##
## $Age
##
## $Outcome
Correlation
vctCorr = numeric(0)
for (i in names(dfrModel)){
cor.result <- cor(as.numeric(dfrModel$Outcome), as.numeric(dfrModel[,i]))
vctCorr <- c(vctCorr, cor.result)
}
dfrCorr <- vctCorr
names(dfrCorr) <- names(dfrModel)
dfrCorr## Pregnancies Glucose BloodPressure
## 0.22788336 0.45937296 0.06027482
## SkinThickness Insulin BMI
## 0.08621860 0.14530972 0.30891558
## DiabetesPedigreeFunction Age Outcome
## 0.17211110 0.22650741 1.00000000_ Observation _
The correlation coefficient shows High correlation of probabilty of a person getting diabetes, only with Glucose levels, followed by her BMI.
dfrGraph <- gather(dfrModel, variable, value, -Outcome)
head(dfrGraph)## Outcome variable value
## 1 1 Pregnancies 6
## 2 0 Pregnancies 1
## 3 1 Pregnancies 8
## 4 0 Pregnancies 1
## 5 1 Pregnancies 0
## 6 0 Pregnancies 5Data Visualization
ggplot(dfrGraph) +
geom_jitter(aes(value,Outcome, colour=variable)) +
facet_wrap(~variable, scales="free_x") +
labs(title="Relation Of Outcome With Other Features")
Summary
lapply(dfrModel, FUN=summary)## $Pregnancies
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 3.000 3.827 6.000 17.000
##
## $Glucose
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0 99.0 116.0 120.5 140.5 199.0
##
## $BloodPressure
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 63.00 72.00 68.88 80.00 122.00
##
## $SkinThickness
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 23.00 20.41 32.00 99.00
##
## $Insulin
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 37.00 79.99 127.00 846.00
##
## $BMI
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 27.00 32.00 31.87 36.50 67.10
##
## $DiabetesPedigreeFunction
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0780 0.2400 0.3750 0.4754 0.6340 2.4200
##
## $Age
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.00 24.00 29.00 33.13 40.00 81.00
##
## $Outcome
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.3448 1.0000 1.0000Find Best Multi Logistic Model
Choose the best logistic model by using step().
stpModel=step(glm(data=dfrModel, formula=Outcome~., family=binomial), trace=0, steps=1000)
summary(stpModel)##
## Call:
## glm(formula = Outcome ~ Pregnancies + Glucose + BloodPressure +
## BMI + DiabetesPedigreeFunction, family = binomial, data = dfrModel)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.7640 -0.7318 -0.4090 0.7146 2.8871
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -8.053940 0.716823 -11.236 < 2e-16 ***
## Pregnancies 0.157926 0.029314 5.387 7.15e-08 ***
## Glucose 0.033384 0.003518 9.488 < 2e-16 ***
## BloodPressure -0.012549 0.005256 -2.388 0.01696 *
## BMI 0.092717 0.015076 6.150 7.75e-10 ***
## DiabetesPedigreeFunction 0.909844 0.305380 2.979 0.00289 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 900.53 on 698 degrees of freedom
## Residual deviance: 657.22 on 693 degrees of freedom
## AIC: 669.22
##
## Number of Fisher Scoring iterations: 5Observation
Logistic Model has been created
Make Final Multi Linear Model
# make model
mgmModel <- glm(data=dfrModel, formula=Outcome~Pregnancies+Glucose+BMI+DiabetesPedigreeFunction, family=binomial(link="logit"))
# print summary
summary(mgmModel)##
## Call:
## glm(formula = Outcome ~ Pregnancies + Glucose + BMI + DiabetesPedigreeFunction,
## family = binomial(link = "logit"), data = dfrModel)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.7331 -0.7281 -0.4124 0.7472 2.8316
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -8.539916 0.696245 -12.266 < 2e-16 ***
## Pregnancies 0.145368 0.028490 5.103 3.35e-07 ***
## Glucose 0.032594 0.003471 9.390 < 2e-16 ***
## BMI 0.085596 0.014644 5.845 5.06e-09 ***
## DiabetesPedigreeFunction 0.904552 0.302902 2.986 0.00282 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 900.53 on 698 degrees of freedom
## Residual deviance: 662.98 on 694 degrees of freedom
## AIC: 672.98
##
## Number of Fisher Scoring iterations: 5Confusion Matrix
prdVal <- predict(mgmModel, type='response')
prdBln <- ifelse(prdVal > 0.6, 1, 0)
cnfmtrx <- table(prd=prdBln, act=dfrModel$Outcome)
confusionMatrix(cnfmtrx)## Confusion Matrix and Statistics
##
## act
## prd 0 1
## 0 426 128
## 1 32 113
##
## Accuracy : 0.7711
## 95% CI : (0.7381, 0.8018)
## No Information Rate : 0.6552
## P-Value [Acc > NIR] : 1.790e-11
##
## Kappa : 0.4406
## Mcnemar's Test P-Value : 5.894e-14
##
## Sensitivity : 0.9301
## Specificity : 0.4689
## Pos Pred Value : 0.7690
## Neg Pred Value : 0.7793
## Prevalence : 0.6552
## Detection Rate : 0.6094
## Detection Prevalence : 0.7926
## Balanced Accuracy : 0.6995
##
## 'Positive' Class : 0
## Obersvation
The confusion Matrix shows an accuracy of 77.1 % of the predicted value as that of the actual ones.
Thus , this model is good to go with.
Regression Data
dfrPlot <- mutate(dfrModel, PrdVal=prdVal, PSurvived=prdBln)
head(dfrPlot)## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## DiabetesPedigreeFunction Age Outcome PrdVal PSurvived
## 1 0.627 50 1 0.64553064 1
## 2 0.351 31 0 0.04610352 0
## 3 0.672 32 1 0.76675038 1
## 4 0.167 21 0 0.05033869 0
## 5 2.288 33 1 0.84347695 1
## 6 0.201 30 0 0.15988997 0Regression Visulaization
#dfrPlot
ggplot(dfrPlot, aes(x=PrdVal, y=Outcome)) +
geom_point(shape=19, colour="blue", fill="blue") +
geom_smooth(method="gam", formula=y~s(log(x)), se=FALSE) +
labs(title="Binomial Regression Curve") +
labs(x="") +
labs(y="")
Test Data
dfrTest <- read.csv("C:/firstproject/train-diabetes.csv", header=T, stringsAsFactors=F)
head(dfrTest)## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## DiabetesPedigreeFunction Age Outcome
## 1 0.627 50 1
## 2 0.351 31 0
## 3 0.672 32 1
## 4 0.167 21 0
## 5 2.288 33 1
## 6 0.201 30 0Observation
Similar Data as in the train dataset , here too, we choose to retain 0 in the values.
Predict
resVal <- predict(mgmModel, dfrTest, type="response")
prdSur <- ifelse(resVal > 0.6, "Diabetic", "Non- Diabetic")
dfrTest <- mutate(dfrTest, Result=resVal, PredictedOutcome=prdSur)
dfrTest ## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## 7 3 78 50 32 88 31.0
## 8 10 115 0 0 0 35.3
## 9 2 197 70 45 543 30.5
## 10 8 125 96 0 0 0.0
## 11 4 110 92 0 0 37.6
## 12 10 168 74 0 0 38.0
## 13 10 139 80 0 0 27.1
## 14 1 189 60 23 846 30.1
## 15 5 166 72 19 175 25.8
## 16 7 100 0 0 0 30.0
## 17 0 118 84 47 230 45.8
## 18 7 107 74 0 0 29.6
## 19 1 103 30 38 83 43.3
## 20 1 115 70 30 96 34.6
## 21 3 126 88 41 235 39.3
## 22 8 99 84 0 0 35.4
## 23 7 196 90 0 0 39.8
## 24 9 119 80 35 0 29.0
## 25 11 143 94 33 146 36.6
## 26 10 125 70 26 115 31.1
## 27 7 147 76 0 0 39.4
## 28 1 97 66 15 140 23.2
## 29 13 145 82 19 110 22.2
## 30 5 117 92 0 0 34.1
## 31 5 109 75 26 0 36.0
## 32 3 158 76 36 245 31.6
## 33 3 88 58 11 54 24.8
## 34 6 92 92 0 0 19.9
## 35 10 122 78 31 0 27.6
## 36 4 103 60 33 192 24.0
## 37 11 138 76 0 0 33.2
## 38 9 102 76 37 0 32.9
## 39 2 90 68 42 0 38.2
## 40 4 111 72 47 207 37.1
## 41 3 180 64 25 70 34.0
## 42 7 133 84 0 0 40.2
## 43 7 106 92 18 0 22.7
## 44 9 171 110 24 240 45.4
## 45 7 159 64 0 0 27.4
## 46 0 180 66 39 0 42.0
## 47 1 146 56 0 0 29.7
## 48 2 71 70 27 0 28.0
## 49 7 103 66 32 0 39.1
## 50 7 105 0 0 0 0.0
## 51 1 103 80 11 82 19.4
## 52 1 101 50 15 36 24.2
## 53 5 88 66 21 23 24.4
## 54 8 176 90 34 300 33.7
## 55 7 150 66 42 342 34.7
## 56 1 73 50 10 0 23.0
## 57 7 187 68 39 304 37.7
## 58 0 100 88 60 110 46.8
## 59 0 146 82 0 0 40.5
## 60 0 105 64 41 142 41.5
## 61 2 84 0 0 0 0.0
## 62 8 133 72 0 0 32.9
## 63 5 44 62 0 0 25.0
## 64 2 141 58 34 128 25.4
## 65 7 114 66 0 0 32.8
## 66 5 99 74 27 0 29.0
## 67 0 109 88 30 0 32.5
## 68 2 109 92 0 0 42.7
## 69 1 95 66 13 38 19.6
## 70 4 146 85 27 100 28.9
## 71 2 100 66 20 90 32.9
## 72 5 139 64 35 140 28.6
## 73 13 126 90 0 0 43.4
## 74 4 129 86 20 270 35.1
## 75 1 79 75 30 0 32.0
## 76 1 0 48 20 0 24.7
## 77 7 62 78 0 0 32.6
## 78 5 95 72 33 0 37.7
## 79 0 131 0 0 0 43.2
## 80 2 112 66 22 0 25.0
## 81 3 113 44 13 0 22.4
## 82 2 74 0 0 0 0.0
## 83 7 83 78 26 71 29.3
## 84 0 101 65 28 0 24.6
## 85 5 137 108 0 0 48.8
## 86 2 110 74 29 125 32.4
## 87 13 106 72 54 0 36.6
## 88 2 100 68 25 71 38.5
## 89 15 136 70 32 110 37.1
## 90 1 107 68 19 0 26.5
## 91 1 80 55 0 0 19.1
## 92 4 123 80 15 176 32.0
## 93 7 81 78 40 48 46.7
## 94 4 134 72 0 0 23.8
## 95 2 142 82 18 64 24.7
## 96 6 144 72 27 228 33.9
## 97 2 92 62 28 0 31.6
## 98 1 71 48 18 76 20.4
## 99 6 93 50 30 64 28.7
## 100 1 122 90 51 220 49.7
## 101 1 163 72 0 0 39.0
## 102 1 151 60 0 0 26.1
## 103 0 125 96 0 0 22.5
## 104 1 81 72 18 40 26.6
## 105 2 85 65 0 0 39.6
## 106 1 126 56 29 152 28.7
## 107 1 96 122 0 0 22.4
## 108 4 144 58 28 140 29.5
## 109 3 83 58 31 18 34.3
## 110 0 95 85 25 36 37.4
## 111 3 171 72 33 135 33.3
## 112 8 155 62 26 495 34.0
## 113 1 89 76 34 37 31.2
## 114 4 76 62 0 0 34.0
## 115 7 160 54 32 175 30.5
## 116 4 146 92 0 0 31.2
## 117 5 124 74 0 0 34.0
## 118 5 78 48 0 0 33.7
## 119 4 97 60 23 0 28.2
## 120 4 99 76 15 51 23.2
## 121 0 162 76 56 100 53.2
## 122 6 111 64 39 0 34.2
## 123 2 107 74 30 100 33.6
## 124 5 132 80 0 0 26.8
## 125 0 113 76 0 0 33.3
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## 127 3 120 70 30 135 42.9
## 128 1 118 58 36 94 33.3
## 129 1 117 88 24 145 34.5
## 130 0 105 84 0 0 27.9
## 131 4 173 70 14 168 29.7
## 132 9 122 56 0 0 33.3
## 133 3 170 64 37 225 34.5
## 134 8 84 74 31 0 38.3
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## 137 0 100 70 26 50 30.8
## 138 0 93 60 25 92 28.7
## 139 0 129 80 0 0 31.2
## 140 5 105 72 29 325 36.9
## 141 3 128 78 0 0 21.1
## 142 5 106 82 30 0 39.5
## 143 2 108 52 26 63 32.5
## 144 10 108 66 0 0 32.4
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## 161 4 151 90 38 0 29.7
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## 163 0 114 80 34 285 44.2
## 164 2 100 64 23 0 29.7
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## 167 3 148 66 25 0 32.5
## 168 4 120 68 0 0 29.6
## 169 4 110 66 0 0 31.9
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## 171 6 102 82 0 0 30.8
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## 173 2 87 0 23 0 28.9
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## 177 6 85 78 0 0 31.2
## 178 0 129 110 46 130 67.1
## 179 5 143 78 0 0 45.0
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## 181 6 87 80 0 0 23.2
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## 183 1 0 74 20 23 27.7
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## 190 5 139 80 35 160 31.6
## 191 3 111 62 0 0 22.6
## 192 9 123 70 44 94 33.1
## 193 7 159 66 0 0 30.4
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## 195 8 85 55 20 0 24.4
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## 197 1 105 58 0 0 24.3
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## 201 0 113 80 16 0 31.0
## 202 1 138 82 0 0 40.1
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## 233 1 79 80 25 37 25.4
## 234 4 122 68 0 0 35.0
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## 236 4 171 72 0 0 43.6
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## 251 9 106 52 0 0 31.2
## 252 2 129 84 0 0 28.0
## 253 2 90 80 14 55 24.4
## 254 0 86 68 32 0 35.8
## 255 12 92 62 7 258 27.6
## 256 1 113 64 35 0 33.6
## 257 3 111 56 39 0 30.1
## 258 2 114 68 22 0 28.7
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## 260 11 155 76 28 150 33.3
## 261 3 191 68 15 130 30.9
## 262 3 141 0 0 0 30.0
## 263 4 95 70 32 0 32.1
## 264 3 142 80 15 0 32.4
## 265 4 123 62 0 0 32.0
## 266 5 96 74 18 67 33.6
## 267 0 138 0 0 0 36.3
## 268 2 128 64 42 0 40.0
## 269 0 102 52 0 0 25.1
## 270 2 146 0 0 0 27.5
## 271 10 101 86 37 0 45.6
## 272 2 108 62 32 56 25.2
## 273 3 122 78 0 0 23.0
## 274 1 71 78 50 45 33.2
## 275 13 106 70 0 0 34.2
## 276 2 100 70 52 57 40.5
## 277 7 106 60 24 0 26.5
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## 279 5 114 74 0 0 24.9
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## 281 0 146 70 0 0 37.9
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## 284 7 161 86 0 0 30.4
## 285 2 108 80 0 0 27.0
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## 318 3 182 74 0 0 30.5
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## 320 6 194 78 0 0 23.5
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## 322 3 112 74 30 0 31.6
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## 324 13 152 90 33 29 26.8
## 325 2 112 75 32 0 35.7
## 326 1 157 72 21 168 25.6
## 327 1 122 64 32 156 35.1
## 328 10 179 70 0 0 35.1
## 329 2 102 86 36 120 45.5
## 330 6 105 70 32 68 30.8
## 331 8 118 72 19 0 23.1
## 332 2 87 58 16 52 32.7
## 333 1 180 0 0 0 43.3
## 334 12 106 80 0 0 23.6
## 335 1 95 60 18 58 23.9
## 336 0 165 76 43 255 47.9
## 337 0 117 0 0 0 33.8
## 338 5 115 76 0 0 31.2
## 339 9 152 78 34 171 34.2
## 340 7 178 84 0 0 39.9
## 341 1 130 70 13 105 25.9
## 342 1 95 74 21 73 25.9
## 343 1 0 68 35 0 32.0
## 344 5 122 86 0 0 34.7
## 345 8 95 72 0 0 36.8
## 346 8 126 88 36 108 38.5
## 347 1 139 46 19 83 28.7
## 348 3 116 0 0 0 23.5
## 349 3 99 62 19 74 21.8
## 350 5 0 80 32 0 41.0
## 351 4 92 80 0 0 42.2
## 352 4 137 84 0 0 31.2
## 353 3 61 82 28 0 34.4
## 354 1 90 62 12 43 27.2
## 355 3 90 78 0 0 42.7
## 356 9 165 88 0 0 30.4
## 357 1 125 50 40 167 33.3
## 358 13 129 0 30 0 39.9
## 359 12 88 74 40 54 35.3
## 360 1 196 76 36 249 36.5
## 361 5 189 64 33 325 31.2
## 362 5 158 70 0 0 29.8
## 363 5 103 108 37 0 39.2
## 364 4 146 78 0 0 38.5
## 365 4 147 74 25 293 34.9
## 366 5 99 54 28 83 34.0
## 367 6 124 72 0 0 27.6
## 368 0 101 64 17 0 21.0
## 369 3 81 86 16 66 27.5
## 370 1 133 102 28 140 32.8
## 371 3 173 82 48 465 38.4
## 372 0 118 64 23 89 0.0
## 373 0 84 64 22 66 35.8
## 374 2 105 58 40 94 34.9
## 375 2 122 52 43 158 36.2
## 376 12 140 82 43 325 39.2
## 377 0 98 82 15 84 25.2
## 378 1 87 60 37 75 37.2
## 379 4 156 75 0 0 48.3
## 380 0 93 100 39 72 43.4
## 381 1 107 72 30 82 30.8
## 382 0 105 68 22 0 20.0
## 383 1 109 60 8 182 25.4
## 384 1 90 62 18 59 25.1
## 385 1 125 70 24 110 24.3
## 386 1 119 54 13 50 22.3
## 387 5 116 74 29 0 32.3
## 388 8 105 100 36 0 43.3
## 389 5 144 82 26 285 32.0
## 390 3 100 68 23 81 31.6
## 391 1 100 66 29 196 32.0
## 392 5 166 76 0 0 45.7
## 393 1 131 64 14 415 23.7
## 394 4 116 72 12 87 22.1
## 395 4 158 78 0 0 32.9
## 396 2 127 58 24 275 27.7
## 397 3 96 56 34 115 24.7
## 398 0 131 66 40 0 34.3
## 399 3 82 70 0 0 21.1
## 400 3 193 70 31 0 34.9
## 401 4 95 64 0 0 32.0
## 402 6 137 61 0 0 24.2
## 403 5 136 84 41 88 35.0
## 404 9 72 78 25 0 31.6
## 405 5 168 64 0 0 32.9
## 406 2 123 48 32 165 42.1
## 407 4 115 72 0 0 28.9
## 408 0 101 62 0 0 21.9
## 409 8 197 74 0 0 25.9
## 410 1 172 68 49 579 42.4
## 411 6 102 90 39 0 35.7
## 412 1 112 72 30 176 34.4
## 413 1 143 84 23 310 42.4
## 414 1 143 74 22 61 26.2
## 415 0 138 60 35 167 34.6
## 416 3 173 84 33 474 35.7
## 417 1 97 68 21 0 27.2
## 418 4 144 82 32 0 38.5
## 419 1 83 68 0 0 18.2
## 420 3 129 64 29 115 26.4
## 421 1 119 88 41 170 45.3
## 422 2 94 68 18 76 26.0
## 423 0 102 64 46 78 40.6
## 424 2 115 64 22 0 30.8
## 425 8 151 78 32 210 42.9
## 426 4 184 78 39 277 37.0
## 427 0 94 0 0 0 0.0
## 428 1 181 64 30 180 34.1
## 429 0 135 94 46 145 40.6
## 430 1 95 82 25 180 35.0
## 431 2 99 0 0 0 22.2
## 432 3 89 74 16 85 30.4
## 433 1 80 74 11 60 30.0
## 434 2 139 75 0 0 25.6
## 435 1 90 68 8 0 24.5
## 436 0 141 0 0 0 42.4
## 437 12 140 85 33 0 37.4
## 438 5 147 75 0 0 29.9
## 439 1 97 70 15 0 18.2
## 440 6 107 88 0 0 36.8
## 441 0 189 104 25 0 34.3
## 442 2 83 66 23 50 32.2
## 443 4 117 64 27 120 33.2
## 444 8 108 70 0 0 30.5
## 445 4 117 62 12 0 29.7
## 446 0 180 78 63 14 59.4
## 447 1 100 72 12 70 25.3
## 448 0 95 80 45 92 36.5
## 449 0 104 64 37 64 33.6
## 450 0 120 74 18 63 30.5
## 451 1 82 64 13 95 21.2
## 452 2 134 70 0 0 28.9
## 453 0 91 68 32 210 39.9
## 454 2 119 0 0 0 19.6
## 455 2 100 54 28 105 37.8
## 456 14 175 62 30 0 33.6
## 457 1 135 54 0 0 26.7
## 458 5 86 68 28 71 30.2
## 459 10 148 84 48 237 37.6
## 460 9 134 74 33 60 25.9
## 461 9 120 72 22 56 20.8
## 462 1 71 62 0 0 21.8
## 463 8 74 70 40 49 35.3
## 464 5 88 78 30 0 27.6
## 465 10 115 98 0 0 24.0
## 466 0 124 56 13 105 21.8
## 467 0 74 52 10 36 27.8
## 468 0 97 64 36 100 36.8
## 469 8 120 0 0 0 30.0
## 470 6 154 78 41 140 46.1
## 471 1 144 82 40 0 41.3
## 472 0 137 70 38 0 33.2
## 473 0 119 66 27 0 38.8
## 474 7 136 90 0 0 29.9
## 475 4 114 64 0 0 28.9
## 476 0 137 84 27 0 27.3
## 477 2 105 80 45 191 33.7
## 478 7 114 76 17 110 23.8
## 479 8 126 74 38 75 25.9
## 480 4 132 86 31 0 28.0
## 481 3 158 70 30 328 35.5
## 482 0 123 88 37 0 35.2
## 483 4 85 58 22 49 27.8
## 484 0 84 82 31 125 38.2
## 485 0 145 0 0 0 44.2
## 486 0 135 68 42 250 42.3
## 487 1 139 62 41 480 40.7
## 488 0 173 78 32 265 46.5
## 489 4 99 72 17 0 25.6
## 490 8 194 80 0 0 26.1
## 491 2 83 65 28 66 36.8
## 492 2 89 90 30 0 33.5
## 493 4 99 68 38 0 32.8
## 494 4 125 70 18 122 28.9
## 495 3 80 0 0 0 0.0
## 496 6 166 74 0 0 26.6
## 497 5 110 68 0 0 26.0
## 498 2 81 72 15 76 30.1
## 499 7 195 70 33 145 25.1
## 500 6 154 74 32 193 29.3
## 501 2 117 90 19 71 25.2
## 502 3 84 72 32 0 37.2
## 503 6 0 68 41 0 39.0
## 504 7 94 64 25 79 33.3
## 505 3 96 78 39 0 37.3
## 506 10 75 82 0 0 33.3
## 507 0 180 90 26 90 36.5
## 508 1 130 60 23 170 28.6
## 509 2 84 50 23 76 30.4
## 510 8 120 78 0 0 25.0
## 511 12 84 72 31 0 29.7
## 512 0 139 62 17 210 22.1
## 513 9 91 68 0 0 24.2
## 514 2 91 62 0 0 27.3
## 515 3 99 54 19 86 25.6
## 516 3 163 70 18 105 31.6
## 517 9 145 88 34 165 30.3
## 518 7 125 86 0 0 37.6
## 519 13 76 60 0 0 32.8
## 520 6 129 90 7 326 19.6
## 521 2 68 70 32 66 25.0
## 522 3 124 80 33 130 33.2
## 523 6 114 0 0 0 0.0
## 524 9 130 70 0 0 34.2
## 525 3 125 58 0 0 31.6
## 526 3 87 60 18 0 21.8
## 527 1 97 64 19 82 18.2
## 528 3 116 74 15 105 26.3
## 529 0 117 66 31 188 30.8
## 530 0 111 65 0 0 24.6
## 531 2 122 60 18 106 29.8
## 532 0 107 76 0 0 45.3
## 533 1 86 66 52 65 41.3
## 534 6 91 0 0 0 29.8
## 535 1 77 56 30 56 33.3
## 536 4 132 0 0 0 32.9
## 537 0 105 90 0 0 29.6
## 538 0 57 60 0 0 21.7
## 539 0 127 80 37 210 36.3
## 540 3 129 92 49 155 36.4
## 541 8 100 74 40 215 39.4
## 542 3 128 72 25 190 32.4
## 543 10 90 85 32 0 34.9
## 544 4 84 90 23 56 39.5
## 545 1 88 78 29 76 32.0
## 546 8 186 90 35 225 34.5
## 547 5 187 76 27 207 43.6
## 548 4 131 68 21 166 33.1
## 549 1 164 82 43 67 32.8
## 550 4 189 110 31 0 28.5
## 551 1 116 70 28 0 27.4
## 552 3 84 68 30 106 31.9
## 553 6 114 88 0 0 27.8
## 554 1 88 62 24 44 29.9
## 555 1 84 64 23 115 36.9
## 556 7 124 70 33 215 25.5
## 557 1 97 70 40 0 38.1
## 558 8 110 76 0 0 27.8
## 559 11 103 68 40 0 46.2
## 560 11 85 74 0 0 30.1
## 561 6 125 76 0 0 33.8
## 562 0 198 66 32 274 41.3
## 563 1 87 68 34 77 37.6
## 564 6 99 60 19 54 26.9
## 565 0 91 80 0 0 32.4
## 566 2 95 54 14 88 26.1
## 567 1 99 72 30 18 38.6
## 568 6 92 62 32 126 32.0
## 569 4 154 72 29 126 31.3
## 570 0 121 66 30 165 34.3
## 571 3 78 70 0 0 32.5
## 572 2 130 96 0 0 22.6
## 573 3 111 58 31 44 29.5
## 574 2 98 60 17 120 34.7
## 575 1 143 86 30 330 30.1
## 576 1 119 44 47 63 35.5
## 577 6 108 44 20 130 24.0
## 578 2 118 80 0 0 42.9
## 579 10 133 68 0 0 27.0
## 580 2 197 70 99 0 34.7
## 581 0 151 90 46 0 42.1
## 582 6 109 60 27 0 25.0
## 583 12 121 78 17 0 26.5
## 584 8 100 76 0 0 38.7
## 585 8 124 76 24 600 28.7
## 586 1 93 56 11 0 22.5
## 587 8 143 66 0 0 34.9
## 588 6 103 66 0 0 24.3
## 589 3 176 86 27 156 33.3
## 590 0 73 0 0 0 21.1
## 591 11 111 84 40 0 46.8
## 592 2 112 78 50 140 39.4
## 593 3 132 80 0 0 34.4
## 594 2 82 52 22 115 28.5
## 595 6 123 72 45 230 33.6
## 596 0 188 82 14 185 32.0
## 597 0 67 76 0 0 45.3
## 598 1 89 24 19 25 27.8
## 599 1 173 74 0 0 36.8
## 600 1 109 38 18 120 23.1
## 601 1 108 88 19 0 27.1
## 602 6 96 0 0 0 23.7
## 603 1 124 74 36 0 27.8
## 604 7 150 78 29 126 35.2
## 605 4 183 0 0 0 28.4
## 606 1 124 60 32 0 35.8
## 607 1 181 78 42 293 40.0
## 608 1 92 62 25 41 19.5
## 609 0 152 82 39 272 41.5
## 610 1 111 62 13 182 24.0
## 611 3 106 54 21 158 30.9
## 612 3 174 58 22 194 32.9
## 613 7 168 88 42 321 38.2
## 614 6 105 80 28 0 32.5
## 615 11 138 74 26 144 36.1
## 616 3 106 72 0 0 25.8
## 617 6 117 96 0 0 28.7
## 618 2 68 62 13 15 20.1
## 619 9 112 82 24 0 28.2
## 620 0 119 0 0 0 32.4
## 621 2 112 86 42 160 38.4
## 622 2 92 76 20 0 24.2
## 623 6 183 94 0 0 40.8
## 624 0 94 70 27 115 43.5
## 625 2 108 64 0 0 30.8
## 626 4 90 88 47 54 37.7
## 627 0 125 68 0 0 24.7
## 628 0 132 78 0 0 32.4
## 629 5 128 80 0 0 34.6
## 630 4 94 65 22 0 24.7
## 631 7 114 64 0 0 27.4
## 632 0 102 78 40 90 34.5
## 633 2 111 60 0 0 26.2
## 634 1 128 82 17 183 27.5
## 635 10 92 62 0 0 25.9
## 636 13 104 72 0 0 31.2
## 637 5 104 74 0 0 28.8
## 638 2 94 76 18 66 31.6
## 639 7 97 76 32 91 40.9
## 640 1 100 74 12 46 19.5
## 641 0 102 86 17 105 29.3
## 642 4 128 70 0 0 34.3
## 643 6 147 80 0 0 29.5
## 644 4 90 0 0 0 28.0
## 645 3 103 72 30 152 27.6
## 646 2 157 74 35 440 39.4
## 647 1 167 74 17 144 23.4
## 648 0 179 50 36 159 37.8
## 649 11 136 84 35 130 28.3
## 650 0 107 60 25 0 26.4
## 651 1 91 54 25 100 25.2
## 652 1 117 60 23 106 33.8
## 653 5 123 74 40 77 34.1
## 654 2 120 54 0 0 26.8
## 655 1 106 70 28 135 34.2
## 656 2 155 52 27 540 38.7
## 657 2 101 58 35 90 21.8
## 658 1 120 80 48 200 38.9
## 659 11 127 106 0 0 39.0
## 660 3 80 82 31 70 34.2
## 661 10 162 84 0 0 27.7
## 662 1 199 76 43 0 42.9
## 663 8 167 106 46 231 37.6
## 664 9 145 80 46 130 37.9
## 665 6 115 60 39 0 33.7
## 666 1 112 80 45 132 34.8
## 667 4 145 82 18 0 32.5
## 668 10 111 70 27 0 27.5
## 669 6 98 58 33 190 34.0
## 670 9 154 78 30 100 30.9
## 671 6 165 68 26 168 33.6
## 672 1 99 58 10 0 25.4
## 673 10 68 106 23 49 35.5
## 674 3 123 100 35 240 57.3
## 675 8 91 82 0 0 35.6
## 676 6 195 70 0 0 30.9
## 677 9 156 86 0 0 24.8
## 678 0 93 60 0 0 35.3
## 679 3 121 52 0 0 36.0
## 680 2 101 58 17 265 24.2
## 681 2 56 56 28 45 24.2
## 682 0 162 76 36 0 49.6
## 683 0 95 64 39 105 44.6
## 684 4 125 80 0 0 32.3
## 685 5 136 82 0 0 0.0
## 686 2 129 74 26 205 33.2
## 687 3 130 64 0 0 23.1
## 688 1 107 50 19 0 28.3
## 689 1 140 74 26 180 24.1
## 690 1 144 82 46 180 46.1
## 691 8 107 80 0 0 24.6
## 692 13 158 114 0 0 42.3
## 693 2 121 70 32 95 39.1
## 694 7 129 68 49 125 38.5
## 695 2 90 60 0 0 23.5
## 696 7 142 90 24 480 30.4
## 697 3 169 74 19 125 29.9
## 698 0 99 0 0 0 25.0
## 699 4 127 88 11 155 34.5
## DiabetesPedigreeFunction Age Outcome Result PredictedOutcome
## 1 0.627 50 1 0.645530636 Diabetic
## 2 0.351 31 0 0.046103517 Non- Diabetic
## 3 0.672 32 1 0.766750379 Diabetic
## 4 0.167 21 0 0.050338689 Non- Diabetic
## 5 2.288 33 1 0.843476948 Diabetic
## 6 0.201 30 0 0.159889972 Non- Diabetic
## 7 0.248 26 1 0.063945962 Non- Diabetic
## 8 0.134 29 0 0.451374074 Non- Diabetic
## 9 0.158 53 1 0.716165106 Diabetic
## 10 0.232 54 1 0.043404442 Non- Diabetic
## 11 0.191 30 0 0.272520796 Non- Diabetic
## 12 0.537 34 1 0.893597390 Diabetic
## 13 1.441 57 0 0.744121789 Diabetic
## 14 0.398 59 1 0.668686166 Diabetic
## 15 0.587 51 1 0.583448794 Non- Diabetic
## 16 0.484 32 1 0.221454870 Non- Diabetic
## 17 0.551 31 1 0.431665370 Non- Diabetic
## 18 0.254 31 1 0.219029141 Non- Diabetic
## 19 0.183 33 0 0.237674268 Non- Diabetic
## 20 0.529 32 1 0.230399997 Non- Diabetic
## 21 0.704 27 0 0.500954974 Non- Diabetic
## 22 0.388 50 0 0.316684459 Non- Diabetic
## 23 0.451 41 1 0.935886824 Diabetic
## 24 0.263 29 1 0.346902849 Non- Diabetic
## 25 0.254 51 1 0.747006746 Diabetic
## 26 0.205 41 1 0.458977825 Non- Diabetic
## 27 0.257 43 1 0.705577209 Diabetic
## 28 0.487 22 0 0.056971669 Non- Diabetic
## 29 0.245 57 0 0.549316124 Non- Diabetic
## 30 0.337 38 0 0.315211872 Non- Diabetic
## 31 0.546 60 0 0.335160764 Non- Diabetic
## 32 0.851 28 1 0.627315298 Diabetic
## 33 0.267 22 0 0.053595640 Non- Diabetic
## 34 0.188 28 0 0.057562307 Non- Diabetic
## 35 0.512 45 0 0.429441211 Non- Diabetic
## 36 0.966 33 0 0.158009442 Non- Diabetic
## 37 0.420 35 0 0.685435989 Diabetic
## 38 0.665 46 1 0.380051499 Non- Diabetic
## 39 0.503 27 1 0.169255033 Non- Diabetic
## 40 1.390 56 1 0.523104331 Non- Diabetic
## 41 0.271 26 0 0.714753446 Diabetic
## 42 0.696 37 0 0.707496003 Diabetic
## 43 0.235 48 0 0.128786753 Non- Diabetic
## 44 0.721 54 1 0.946863491 Diabetic
## 45 0.294 40 0 0.567447311 Non- Diabetic
## 46 1.893 25 1 0.933045011 Diabetic
## 47 0.564 29 0 0.358152540 Non- Diabetic
## 48 0.586 22 0 0.047056160 Non- Diabetic
## 49 0.344 31 1 0.375865301 Non- Diabetic
## 50 0.305 24 0 0.021372583 Non- Diabetic
## 51 0.491 22 0 0.050564203 Non- Diabetic
## 52 0.526 26 0 0.072071842 Non- Diabetic
## 53 0.342 30 0 0.072637521 Non- Diabetic
## 54 0.467 58 1 0.841130093 Diabetic
## 55 0.718 42 0 0.728391682 Diabetic
## 56 0.248 21 0 0.021412947 Non- Diabetic
## 57 0.254 41 1 0.883864520 Diabetic
## 58 0.962 31 0 0.400257796 Non- Diabetic
## 59 1.781 44 0 0.785248765 Diabetic
## 60 0.173 22 0 0.196427926 Non- Diabetic
## 61 0.304 21 0 0.005291914 Non- Diabetic
## 62 0.270 39 1 0.504607215 Non- Diabetic
## 63 0.587 36 0 0.023938401 Non- Diabetic
## 64 0.699 24 0 0.300074073 Non- Diabetic
## 65 0.258 42 1 0.317421726 Non- Diabetic
## 66 0.203 32 0 0.127826516 Non- Diabetic
## 67 0.855 38 1 0.192809524 Non- Diabetic
## 68 0.845 54 0 0.431169057 Non- Diabetic
## 69 0.334 25 0 0.034949568 Non- Diabetic
## 70 0.189 27 0 0.364711872 Non- Diabetic
## 71 0.867 28 1 0.199507312 Non- Diabetic
## 72 0.411 26 0 0.386361693 Non- Diabetic
## 73 0.583 42 1 0.845403628 Diabetic
## 74 0.231 23 0 0.368097681 Non- Diabetic
## 75 0.396 22 0 0.061669839 Non- Diabetic
## 76 0.140 22 0 0.002121136 Non- Diabetic
## 77 0.391 41 0 0.086482014 Non- Diabetic
## 78 0.370 27 0 0.239587332 Non- Diabetic
## 79 0.270 26 1 0.418712099 Non- Diabetic
## 80 0.307 24 0 0.101469314 Non- Diabetic
## 81 0.140 22 0 0.084970472 Non- Diabetic
## 82 0.102 22 0 0.003188750 Non- Diabetic
## 83 0.767 36 0 0.165862159 Non- Diabetic
## 84 0.237 22 0 0.050794559 Non- Diabetic
## 85 0.227 37 1 0.737843218 Diabetic
## 86 0.698 27 0 0.221128805 Non- Diabetic
## 87 0.178 45 0 0.524657626 Non- Diabetic
## 88 0.324 26 0 0.197624420 Non- Diabetic
## 89 0.153 43 1 0.800186795 Diabetic
## 90 0.165 24 0 0.076604894 Non- Diabetic
## 91 0.258 21 0 0.019479254 Non- Diabetic
## 92 0.443 34 0 0.307989291 Non- Diabetic
## 93 0.261 42 0 0.343269763 Non- Diabetic
## 94 0.277 60 1 0.213653124 Non- Diabetic
## 95 0.761 21 0 0.306148847 Non- Diabetic
## 96 0.255 40 0 0.539482374 Non- Diabetic
## 97 0.130 24 0 0.081057760 Non- Diabetic
## 98 0.323 22 0 0.017258999 Non- Diabetic
## 99 0.356 23 0 0.134960295 Non- Diabetic
## 100 0.325 31 1 0.532474996 Non- Diabetic
## 101 1.222 33 1 0.796077035 Diabetic
## 102 0.179 22 0 0.254108424 Non- Diabetic
## 103 0.262 21 0 0.090898774 Non- Diabetic
## 104 0.283 24 0 0.038362657 Non- Diabetic
## 105 0.930 27 0 0.223079553 Non- Diabetic
## 106 0.801 21 0 0.248524624 Non- Diabetic
## 107 0.207 27 0 0.040664392 Non- Diabetic
## 108 0.287 37 0 0.382215330 Non- Diabetic
## 109 0.336 25 0 0.103530830 Non- Diabetic
## 110 0.247 24 1 0.117251081 Non- Diabetic
## 111 0.199 24 1 0.622503822 Diabetic
## 112 0.543 46 1 0.745850771 Diabetic
## 113 0.192 23 0 0.066027916 Non- Diabetic
## 114 0.391 25 0 0.098206308 Non- Diabetic
## 115 0.588 39 1 0.697479706 Diabetic
## 116 0.539 61 1 0.489624926 Non- Diabetic
## 117 0.220 38 1 0.340268903 Non- Diabetic
## 118 0.654 25 0 0.142516985 Non- Diabetic
## 119 0.443 22 0 0.121078554 Non- Diabetic
## 120 0.223 21 0 0.072827199 Non- Diabetic
## 121 0.759 25 1 0.878750651 Diabetic
## 122 0.260 24 0 0.291697646 Non- Diabetic
## 123 0.404 23 0 0.179445915 Non- Diabetic
## 124 0.186 69 0 0.259534417 Non- Diabetic
## 125 0.278 23 1 0.147426624 Non- Diabetic
## 126 0.496 26 1 0.408592716 Non- Diabetic
## 127 0.452 30 0 0.472142285 Non- Diabetic
## 128 0.261 23 0 0.188166809 Non- Diabetic
## 129 0.403 40 1 0.220389429 Non- Diabetic
## 130 0.741 62 1 0.113136452 Non- Diabetic
## 131 0.361 33 1 0.633935283 Diabetic
## 132 1.114 33 1 0.646328604 Diabetic
## 133 0.356 30 1 0.670914744 Diabetic
## 134 0.457 39 0 0.279423558 Non- Diabetic
## 135 0.647 26 0 0.061295607 Non- Diabetic
## 136 0.088 31 0 0.231097132 Non- Diabetic
## 137 0.597 21 0 0.108699514 Non- Diabetic
## 138 0.532 22 0 0.071041289 Non- Diabetic
## 139 0.703 29 0 0.263329073 Non- Diabetic
## 140 0.159 28 0 0.251931529 Non- Diabetic
## 141 0.268 55 0 0.132018335 Non- Diabetic
## 142 0.286 38 0 0.327764317 Non- Diabetic
## 143 0.318 22 0 0.159834625 Non- Diabetic
## 144 0.272 42 1 0.366634492 Non- Diabetic
## 145 0.237 23 0 0.520745134 Non- Diabetic
## 146 0.572 21 0 0.009032188 Non- Diabetic
## 147 0.096 41 0 0.077320314 Non- Diabetic
## 148 1.400 34 0 0.285545982 Non- Diabetic
## 149 0.218 65 0 0.515017020 Non- Diabetic
## 150 0.085 22 0 0.052053837 Non- Diabetic
## 151 0.399 24 0 0.401433843 Non- Diabetic
## 152 0.432 37 0 0.121600649 Non- Diabetic
## 153 1.189 42 1 0.865830569 Diabetic
## 154 0.687 23 0 0.665750906 Diabetic
## 155 0.137 43 1 0.951420723 Diabetic
## 156 0.337 36 1 0.882534874 Diabetic
## 157 0.637 21 0 0.087826447 Non- Diabetic
## 158 0.833 23 0 0.126613144 Non- Diabetic
## 159 0.229 22 0 0.063480436 Non- Diabetic
## 160 0.817 47 1 0.970232974 Diabetic
## 161 0.294 36 0 0.443111362 Non- Diabetic
## 162 0.204 45 0 0.303856543 Non- Diabetic
## 163 0.167 27 0 0.291163654 Non- Diabetic
## 164 0.368 21 0 0.107680458 Non- Diabetic
## 165 0.743 32 1 0.290464848 Non- Diabetic
## 166 0.722 41 1 0.256264517 Non- Diabetic
## 167 0.256 22 0 0.433791442 Non- Diabetic
## 168 0.709 34 0 0.294809203 Non- Diabetic
## 169 0.471 29 0 0.228553802 Non- Diabetic
## 170 0.495 29 0 0.166985064 Non- Diabetic
## 171 0.180 36 1 0.175969875 Non- Diabetic
## 172 0.542 29 1 0.554857351 Non- Diabetic
## 173 0.773 25 0 0.096170635 Non- Diabetic
## 174 0.678 23 0 0.184995052 Non- Diabetic
## 175 0.370 33 0 0.050800823 Non- Diabetic
## 176 0.719 36 1 0.870658588 Diabetic
## 177 0.382 42 0 0.132269416 Non- Diabetic
## 178 0.319 26 1 0.845119588 Diabetic
## 179 0.190 47 0 0.705082714 Diabetic
## 180 0.956 37 1 0.653794727 Diabetic
## 181 0.084 32 0 0.058957080 Non- Diabetic
## 182 0.725 23 0 0.265402785 Non- Diabetic
## 183 0.299 21 0 0.003162997 Non- Diabetic
## 184 0.268 27 0 0.052287995 Non- Diabetic
## 185 0.244 40 0 0.314434615 Non- Diabetic
## 186 0.745 41 1 0.927423444 Diabetic
## 187 0.615 60 1 0.839614047 Diabetic
## 188 1.321 33 1 0.428377768 Non- Diabetic
## 189 0.640 31 1 0.297938698 Non- Diabetic
## 190 0.361 25 1 0.437560102 Non- Diabetic
## 191 0.142 21 0 0.081442080 Non- Diabetic
## 192 0.374 40 0 0.487264418 Non- Diabetic
## 193 0.383 36 1 0.647652859 Diabetic
## 194 0.578 40 1 0.921209438 Diabetic
## 195 0.136 42 0 0.083564036 Non- Diabetic
## 196 0.395 29 1 0.743955326 Diabetic
## 197 0.187 21 0 0.061629926 Non- Diabetic
## 198 0.678 23 1 0.114784802 Non- Diabetic
## 199 0.905 26 1 0.352450568 Non- Diabetic
## 200 0.150 29 1 0.412444986 Non- Diabetic
## 201 0.874 21 0 0.195810511 Non- Diabetic
## 202 0.236 28 0 0.437666636 Non- Diabetic
## 203 0.787 32 0 0.122274878 Non- Diabetic
## 204 0.235 27 0 0.044633850 Non- Diabetic
## 205 0.324 55 0 0.312076446 Non- Diabetic
## 206 0.407 27 0 0.144155646 Non- Diabetic
## 207 0.605 57 1 0.940957597 Diabetic
## 208 0.151 52 1 0.696520266 Diabetic
## 209 0.289 21 0 0.103189807 Non- Diabetic
## 210 0.355 41 1 0.862333855 Diabetic
## 211 0.290 25 0 0.048535966 Non- Diabetic
## 212 0.375 24 0 0.563206686 Non- Diabetic
## 213 0.164 60 0 0.800239920 Diabetic
## 214 0.431 24 1 0.514886014 Non- Diabetic
## 215 0.260 36 1 0.396886704 Non- Diabetic
## 216 0.742 38 1 0.914928733 Diabetic
## 217 0.514 25 1 0.324975349 Non- Diabetic
## 218 0.464 32 0 0.353015953 Non- Diabetic
## 219 1.224 32 1 0.189526758 Non- Diabetic
## 220 0.261 41 1 0.333838310 Non- Diabetic
## 221 1.072 21 1 0.761441670 Diabetic
## 222 0.805 66 1 0.582668834 Non- Diabetic
## 223 0.209 37 0 0.214581081 Non- Diabetic
## 224 0.687 61 0 0.548017401 Non- Diabetic
## 225 0.666 26 0 0.074979176 Non- Diabetic
## 226 0.101 22 0 0.075449493 Non- Diabetic
## 227 0.198 26 0 0.117845385 Non- Diabetic
## 228 0.652 24 1 0.721201209 Diabetic
## 229 2.329 31 0 0.976124416 Diabetic
## 230 0.089 24 0 0.314985205 Non- Diabetic
## 231 0.645 22 1 0.734900963 Diabetic
## 232 0.238 46 1 0.704698523 Diabetic
## 233 0.583 22 0 0.042367127 Non- Diabetic
## 234 0.394 29 0 0.347586567 Non- Diabetic
## 235 0.293 23 0 0.052920978 Non- Diabetic
## 236 0.479 26 1 0.855755458 Diabetic
## 237 0.586 51 1 0.878704388 Diabetic
## 238 0.686 23 1 0.844197455 Diabetic
## 239 0.831 32 1 0.817861247 Diabetic
## 240 0.582 27 0 0.045274493 Non- Diabetic
## 241 0.192 21 0 0.059783923 Non- Diabetic
## 242 0.446 22 0 0.147331424 Non- Diabetic
## 243 0.402 22 1 0.265359016 Non- Diabetic
## 244 1.318 33 1 0.431160759 Non- Diabetic
## 245 0.329 29 0 0.519234502 Non- Diabetic
## 246 1.213 49 1 0.919151416 Diabetic
## 247 0.258 41 0 0.448745526 Non- Diabetic
## 248 0.427 23 0 0.845676678 Diabetic
## 249 0.282 34 0 0.523805462 Non- Diabetic
## 250 0.143 23 0 0.111970250 Non- Diabetic
## 251 0.380 42 0 0.318155090 Non- Diabetic
## 252 0.284 27 0 0.199261580 Non- Diabetic
## 253 0.249 24 0 0.047340013 Non- Diabetic
## 254 0.238 25 0 0.078915976 Non- Diabetic
## 255 0.926 44 1 0.355089583 Non- Diabetic
## 256 0.543 21 1 0.206824263 Non- Diabetic
## 257 0.557 30 0 0.196936702 Non- Diabetic
## 258 0.092 25 0 0.119877811 Non- Diabetic
## 259 0.655 24 0 0.669426261 Diabetic
## 260 1.353 51 1 0.898937833 Diabetic
## 261 0.299 34 0 0.738290144 Diabetic
## 262 0.761 27 1 0.437392456 Non- Diabetic
## 263 0.612 24 0 0.173539105 Non- Diabetic
## 264 0.200 63 0 0.372576513 Non- Diabetic
## 265 0.226 35 1 0.267797869 Non- Diabetic
## 266 0.997 43 0 0.287790342 Non- Diabetic
## 267 0.933 25 1 0.477315780 Non- Diabetic
## 268 1.101 24 0 0.584837708 Non- Diabetic
## 269 0.078 21 0 0.047594794 Non- Diabetic
## 270 0.240 28 1 0.285078081 Non- Diabetic
## 271 1.136 38 1 0.757047843 Diabetic
## 272 0.128 21 0 0.078987983 Non- Diabetic
## 273 0.254 40 0 0.126880518 Non- Diabetic
## 274 0.422 21 0 0.054329451 Non- Diabetic
## 275 0.251 52 0 0.489829297 Non- Diabetic
## 276 0.677 25 0 0.286854784 Non- Diabetic
## 277 0.296 29 1 0.177805756 Non- Diabetic
## 278 0.454 23 0 0.086285480 Non- Diabetic
## 279 0.744 57 0 0.215348577 Non- Diabetic
## 280 0.881 22 0 0.145979340 Non- Diabetic
## 281 0.334 28 1 0.441539450 Non- Diabetic
## 282 0.280 39 0 0.609360048 Diabetic
## 283 0.262 37 0 0.455871753 Non- Diabetic
## 284 0.165 47 1 0.616976456 Diabetic
## 285 0.259 52 1 0.101232219 Non- Diabetic
## 286 0.647 51 0 0.430759106 Non- Diabetic
## 287 0.619 34 0 0.752417612 Diabetic
## 288 0.808 29 1 0.529528948 Non- Diabetic
## 289 0.340 26 0 0.060572351 Non- Diabetic
## 290 0.263 33 0 0.275886658 Non- Diabetic
## 291 0.434 21 0 0.079696758 Non- Diabetic
## 292 0.757 25 1 0.225351743 Non- Diabetic
## 293 1.224 31 1 0.676206545 Diabetic
## 294 0.613 24 1 0.449837719 Non- Diabetic
## 295 0.254 65 0 0.233633442 Non- Diabetic
## 296 0.692 28 0 0.714769561 Diabetic
## 297 0.337 29 1 0.312411242 Non- Diabetic
## 298 0.520 24 0 0.208358079 Non- Diabetic
## 299 0.412 46 1 0.564679984 Non- Diabetic
## 300 0.840 58 0 0.279588455 Non- Diabetic
## 301 0.839 30 1 0.605162785 Diabetic
## 302 0.422 25 1 0.384846937 Non- Diabetic
## 303 0.156 35 0 0.109306070 Non- Diabetic
## 304 0.209 28 1 0.657545659 Diabetic
## 305 0.207 37 0 0.226200481 Non- Diabetic
## 306 0.215 29 0 0.321867718 Non- Diabetic
## 307 0.326 47 1 0.654538617 Diabetic
## 308 0.143 21 0 0.139152415 Non- Diabetic
## 309 1.391 25 1 0.377795199 Non- Diabetic
## 310 0.875 30 1 0.354372190 Non- Diabetic
## 311 0.313 41 0 0.073480971 Non- Diabetic
## 312 0.605 22 0 0.237730412 Non- Diabetic
## 313 0.433 27 1 0.370862322 Non- Diabetic
## 314 0.626 25 0 0.209274151 Non- Diabetic
## 315 1.127 43 1 0.530658094 Non- Diabetic
## 316 0.315 26 0 0.198636029 Non- Diabetic
## 317 0.284 30 0 0.048889534 Non- Diabetic
## 318 0.345 29 1 0.679423131 Diabetic
## 319 0.150 28 0 0.277167531 Non- Diabetic
## 320 0.129 59 1 0.686498801 Diabetic
## 321 0.527 31 0 0.284312109 Non- Diabetic
## 322 0.197 25 1 0.172187757 Non- Diabetic
## 323 0.254 36 1 0.127514214 Non- Diabetic
## 324 0.731 43 1 0.778926915 Diabetic
## 325 0.148 21 0 0.196400189 Non- Diabetic
## 326 0.123 24 0 0.273943466 Non- Diabetic
## 327 0.692 30 1 0.312672762 Non- Diabetic
## 328 0.200 37 0 0.873636290 Diabetic
## 329 0.127 23 1 0.285969228 Non- Diabetic
## 330 0.122 37 0 0.182638125 Non- Diabetic
## 331 1.476 46 0 0.445605856 Non- Diabetic
## 332 0.166 25 0 0.078398132 Non- Diabetic
## 333 0.282 41 1 0.807499481 Diabetic
## 334 0.137 44 0 0.232098963 Non- Diabetic
## 335 0.260 22 0 0.046657225 Non- Diabetic
## 336 0.259 26 0 0.763596337 Diabetic
## 337 0.932 44 0 0.270877267 Non- Diabetic
## 338 0.343 44 1 0.252777123 Non- Diabetic
## 339 0.893 33 1 0.811211497 Diabetic
## 340 0.331 41 1 0.880182508 Diabetic
## 341 0.472 22 0 0.180437470 Non- Diabetic
## 342 0.673 36 0 0.077817692 Non- Diabetic
## 343 0.389 22 0 0.004949075 Non- Diabetic
## 344 0.290 33 0 0.353417945 Non- Diabetic
## 345 0.485 57 0 0.333621240 Non- Diabetic
## 346 0.349 49 0 0.584449951 Non- Diabetic
## 347 0.654 22 0 0.306668915 Non- Diabetic
## 348 0.187 23 0 0.105062402 Non- Diabetic
## 349 0.279 26 0 0.059602861 Non- Diabetic
## 350 0.346 37 1 0.018152125 Non- Diabetic
## 351 0.237 29 0 0.243568030 Non- Diabetic
## 352 0.252 30 0 0.355611758 Non- Diabetic
## 353 0.243 46 0 0.049678219 Non- Diabetic
## 354 0.580 24 0 0.068612929 Non- Diabetic
## 355 0.559 21 0 0.267036719 Non- Diabetic
## 356 0.302 49 1 0.735317598 Diabetic
## 357 0.962 28 1 0.354408953 Non- Diabetic
## 358 0.569 44 1 0.815255624 Diabetic
## 359 0.378 48 0 0.362686913 Non- Diabetic
## 360 0.875 29 1 0.870985126 Diabetic
## 361 0.583 29 1 0.824222243 Diabetic
## 362 0.207 63 0 0.518703325 Non- Diabetic
## 363 0.305 65 0 0.304790262 Non- Diabetic
## 364 0.520 67 1 0.637876813 Diabetic
## 365 0.385 30 0 0.542024049 Non- Diabetic
## 366 0.499 30 0 0.227130544 Non- Diabetic
## 367 0.368 29 1 0.282788605 Non- Diabetic
## 368 0.252 21 0 0.038330878 Non- Diabetic
## 369 0.306 22 0 0.055568062 Non- Diabetic
## 370 0.234 45 1 0.261097571 Non- Diabetic
## 371 2.137 25 1 0.940191777 Diabetic
## 372 1.731 21 0 0.041966855 Non- Diabetic
## 373 0.545 21 0 0.095811172 Non- Diabetic
## 374 0.225 25 0 0.163019060 Non- Diabetic
## 375 0.816 28 0 0.392702917 Non- Diabetic
## 376 0.528 58 1 0.832115395 Diabetic
## 377 0.299 22 0 0.051262188 Non- Diabetic
## 378 0.509 22 0 0.128505644 Non- Diabetic
## 379 0.238 32 1 0.813947222 Diabetic
## 380 1.021 35 0 0.295210464 Non- Diabetic
## 381 0.821 24 0 0.178294415 Non- Diabetic
## 382 0.236 22 0 0.039463856 Non- Diabetic
## 383 0.947 21 0 0.140516815 Non- Diabetic
## 384 1.268 25 0 0.102881071 Non- Diabetic
## 385 0.221 25 0 0.115030602 Non- Diabetic
## 386 0.205 24 0 0.081541353 Non- Diabetic
## 387 0.660 35 1 0.338415769 Non- Diabetic
## 388 0.239 45 1 0.491987782 Non- Diabetic
## 389 0.452 58 1 0.507113107 Non- Diabetic
## 390 0.949 28 0 0.217361282 Non- Diabetic
## 391 0.444 42 0 0.119791420 Non- Diabetic
## 392 0.340 27 1 0.860192617 Diabetic
## 393 0.389 21 0 0.148782542 Non- Diabetic
## 394 0.463 37 0 0.133888078 Non- Diabetic
## 395 0.803 31 1 0.675669621 Diabetic
## 396 1.600 25 0 0.427662755 Non- Diabetic
## 397 0.944 39 0 0.118509046 Non- Diabetic
## 398 0.196 22 1 0.239247941 Non- Diabetic
## 399 0.389 25 0 0.036504946 Non- Diabetic
## 400 0.241 25 1 0.800944920 Diabetic
## 401 0.161 31 1 0.121611003 Non- Diabetic
## 402 0.151 55 0 0.270071536 Non- Diabetic
## 403 0.286 35 1 0.468624524 Non- Diabetic
## 404 0.280 38 0 0.127117606 Non- Diabetic
## 405 0.135 41 1 0.645887994 Diabetic
## 406 0.520 26 0 0.458570431 Non- Diabetic
## 407 0.376 46 1 0.198412650 Non- Diabetic
## 408 0.336 25 0 0.044387458 Non- Diabetic
## 409 1.191 39 1 0.912006648 Diabetic
## 410 0.702 28 1 0.813962141 Diabetic
## 411 0.674 28 0 0.336791910 Non- Diabetic
## 412 0.528 25 0 0.210508856 Non- Diabetic
## 413 1.076 22 0 0.704543726 Diabetic
## 414 0.256 21 0 0.221083400 Non- Diabetic
## 415 0.534 21 1 0.354977873 Non- Diabetic
## 416 0.258 22 1 0.695122466 Diabetic
## 417 1.095 22 0 0.128510935 Non- Diabetic
## 418 0.554 37 1 0.629885763 Diabetic
## 419 0.624 27 0 0.027466926 Non- Diabetic
## 420 0.219 28 1 0.191344471 Non- Diabetic
## 421 0.507 26 0 0.455196603 Non- Diabetic
## 422 0.561 21 0 0.079266837 Non- Diabetic
## 423 0.496 21 0 0.215612404 Non- Diabetic
## 424 0.421 21 0 0.184877716 Non- Diabetic
## 425 0.516 36 1 0.843382128 Diabetic
## 426 0.264 31 1 0.809194797 Diabetic
## 427 0.256 25 0 0.005248865 Non- Diabetic
## 428 0.328 38 1 0.672730483 Diabetic
## 429 0.284 26 0 0.399494458 Non- Diabetic
## 430 0.233 43 1 0.109930622 Non- Diabetic
## 431 0.108 23 0 0.046335359 Non- Diabetic
## 432 0.551 38 0 0.108866149 Non- Diabetic
## 433 0.527 22 0 0.060516796 Non- Diabetic
## 434 0.167 29 0 0.201614177 Non- Diabetic
## 435 1.138 36 0 0.088300529 Non- Diabetic
## 436 0.205 29 1 0.467697071 Non- Diabetic
## 437 0.244 41 0 0.766692434 Diabetic
## 438 0.434 28 0 0.482557863 Non- Diabetic
## 439 0.147 21 0 0.028138580 Non- Diabetic
## 440 0.727 31 0 0.407923910 Non- Diabetic
## 441 0.435 41 1 0.721085755 Diabetic
## 442 0.497 22 0 0.088017734 Non- Diabetic
## 443 0.230 24 0 0.250667311 Non- Diabetic
## 444 0.955 33 1 0.405586029 Non- Diabetic
## 445 0.380 30 1 0.221152806 Non- Diabetic
## 446 2.420 25 1 0.990053206 Diabetic
## 447 0.658 28 0 0.085151347 Non- Diabetic
## 448 0.330 26 0 0.117048477 Non- Diabetic
## 449 0.510 22 1 0.140306933 Non- Diabetic
## 450 0.285 26 0 0.146777049 Non- Diabetic
## 451 0.415 23 0 0.028421447 Non- Diabetic
## 452 0.542 23 1 0.285460825 Non- Diabetic
## 453 0.381 25 0 0.140167462 Non- Diabetic
## 454 0.832 72 0 0.125628672 Non- Diabetic
## 455 0.498 24 0 0.213537278 Non- Diabetic
## 456 0.212 38 1 0.906111575 Diabetic
## 457 0.687 62 0 0.252097087 Non- Diabetic
## 458 0.364 24 0 0.109516186 Non- Diabetic
## 459 1.001 51 1 0.865484666 Diabetic
## 460 0.460 81 0 0.442525723 Non- Diabetic
## 461 0.733 48 0 0.293833521 Non- Diabetic
## 462 0.416 26 0 0.021081476 Non- Diabetic
## 463 0.705 39 0 0.213202813 Non- Diabetic
## 464 0.258 37 0 0.087150312 Non- Diabetic
## 465 1.022 34 0 0.411173229 Non- Diabetic
## 466 0.452 21 0 0.097672550 Non- Diabetic
## 467 0.269 22 0 0.029169458 Non- Diabetic
## 468 0.600 25 0 0.156357269 Non- Diabetic
## 469 0.183 38 1 0.324707147 Non- Diabetic
## 470 0.571 27 0 0.859882764 Diabetic
## 471 0.607 28 0 0.594652663 Non- Diabetic
## 472 0.170 22 0 0.253711350 Non- Diabetic
## 473 0.259 22 0 0.248660520 Non- Diabetic
## 474 0.210 50 0 0.415756532 Non- Diabetic
## 475 0.126 24 0 0.160437389 Non- Diabetic
## 476 0.231 59 0 0.178175748 Non- Diabetic
## 477 0.711 29 1 0.214327018 Non- Diabetic
## 478 0.466 31 0 0.206219394 Non- Diabetic
## 479 0.162 39 0 0.287696642 Non- Diabetic
## 480 0.419 63 0 0.293119371 Non- Diabetic
## 481 0.344 35 1 0.597710522 Non- Diabetic
## 482 0.197 29 0 0.207572445 Non- Diabetic
## 483 0.306 28 0 0.073675763 Non- Diabetic
## 484 0.233 23 0 0.089362174 Non- Diabetic
## 485 0.630 31 1 0.631694570 Diabetic
## 486 0.365 24 1 0.452942317 Non- Diabetic
## 487 0.536 21 0 0.526146218 Non- Diabetic
## 488 1.159 58 0 0.893548870 Diabetic
## 489 0.294 28 0 0.093265788 Non- Diabetic
## 490 0.551 67 0 0.842746774 Diabetic
## 491 0.629 24 0 0.138842392 Non- Diabetic
## 492 0.292 42 0 0.098263129 Non- Diabetic
## 493 0.145 33 0 0.142719943 Non- Diabetic
## 494 1.144 45 1 0.407187188 Non- Diabetic
## 495 0.174 22 0 0.004778350 Non- Diabetic
## 496 0.304 66 0 0.573171940 Non- Diabetic
## 497 0.292 30 0 0.149559470 Non- Diabetic
## 498 0.547 25 0 0.073250669 Non- Diabetic
## 499 0.163 55 1 0.755741598 Diabetic
## 500 0.839 39 0 0.649926808 Diabetic
## 501 0.313 21 0 0.119677674 Non- Diabetic
## 502 0.267 28 0 0.125627566 Non- Diabetic
## 503 0.727 41 1 0.024799029 Non- Diabetic
## 504 0.738 41 0 0.280789225 Non- Diabetic
## 505 0.238 40 0 0.172683807 Non- Diabetic
## 506 0.263 38 0 0.174595688 Non- Diabetic
## 507 0.314 35 1 0.675981633 Diabetic
## 508 0.692 21 0 0.252886783 Non- Diabetic
## 509 0.968 21 0 0.115728473 Non- Diabetic
## 510 0.409 64 0 0.277724725 Non- Diabetic
## 511 0.297 46 1 0.223270719 Non- Diabetic
## 512 0.207 21 0 0.126708772 Non- Diabetic
## 513 0.200 58 0 0.117826813 Non- Diabetic
## 514 0.525 22 0 0.077886040 Non- Diabetic
## 515 0.154 24 0 0.072668609 Non- Diabetic
## 516 0.268 28 1 0.539004263 Non- Diabetic
## 517 0.771 53 1 0.686877137 Diabetic
## 518 0.304 51 0 0.511339042 Non- Diabetic
## 519 0.180 41 0 0.231017042 Non- Diabetic
## 520 0.582 60 0 0.221163990 Non- Diabetic
## 521 0.187 25 0 0.023575198 Non- Diabetic
## 522 0.305 26 0 0.280007828 Non- Diabetic
## 523 0.189 26 0 0.022291872 Non- Diabetic
## 524 0.652 45 1 0.627808938 Diabetic
## 525 0.151 24 0 0.233601863 Non- Diabetic
## 526 0.444 21 0 0.047404193 Non- Diabetic
## 527 0.299 21 0 0.032152642 Non- Diabetic
## 528 0.107 24 0 0.121864212 Non- Diabetic
## 529 0.493 22 0 0.161912894 Non- Diabetic
## 530 0.660 31 0 0.098033596 Non- Diabetic
## 531 0.717 22 0 0.254769933 Non- Diabetic
## 532 0.686 24 0 0.364871670 Non- Diabetic
## 533 0.917 29 0 0.226736954 Non- Diabetic
## 534 0.501 31 0 0.154770148 Non- Diabetic
## 535 1.251 24 0 0.129788664 Non- Diabetic
## 536 0.302 23 1 0.362000424 Non- Diabetic
## 537 0.197 46 0 0.082742200 Non- Diabetic
## 538 0.735 67 0 0.015371480 Non- Diabetic
## 539 0.804 23 0 0.362154691 Non- Diabetic
## 540 0.968 32 1 0.523027491 Non- Diabetic
## 541 0.661 43 1 0.463284102 Non- Diabetic
## 542 0.549 27 1 0.340332730 Non- Diabetic
## 543 0.825 56 1 0.396714723 Non- Diabetic
## 544 0.159 25 0 0.155036033 Non- Diabetic
## 545 0.365 29 0 0.078928248 Non- Diabetic
## 546 0.423 37 1 0.883013411 Diabetic
## 547 1.034 53 1 0.950234120 Diabetic
## 548 0.160 28 0 0.329463257 Non- Diabetic
## 549 0.341 50 0 0.516728879 Non- Diabetic
## 550 0.680 37 0 0.778420057 Diabetic
## 551 0.204 21 0 0.110687994 Non- Diabetic
## 552 0.591 25 0 0.109021937 Non- Diabetic
## 553 0.247 66 0 0.206042729 Non- Diabetic
## 554 0.422 23 0 0.070097561 Non- Diabetic
## 555 0.471 28 0 0.111841103 Non- Diabetic
## 556 0.161 37 0 0.240069716 Non- Diabetic
## 557 0.218 30 0 0.144985985 Non- Diabetic
## 558 0.237 58 0 0.231896635 Non- Diabetic
## 559 0.126 42 0 0.618899425 Diabetic
## 560 0.300 35 0 0.210397922 Non- Diabetic
## 561 0.121 54 1 0.356450531 Non- Diabetic
## 562 0.502 28 1 0.870228710 Diabetic
## 563 0.401 24 0 0.121565343 Non- Diabetic
## 564 0.497 32 0 0.155938944 Non- Diabetic
## 565 0.601 27 0 0.094758419 Non- Diabetic
## 566 0.748 22 0 0.096037837 Non- Diabetic
## 567 0.412 21 0 0.183770054 Non- Diabetic
## 568 0.085 46 0 0.135514645 Non- Diabetic
## 569 0.338 37 0 0.511496317 Non- Diabetic
## 570 0.203 33 1 0.185968946 Non- Diabetic
## 571 0.270 39 0 0.073417543 Non- Diabetic
## 572 0.268 21 0 0.137641959 Non- Diabetic
## 573 0.430 22 0 0.171961782 Non- Diabetic
## 574 0.198 22 0 0.129471822 Non- Diabetic
## 575 0.892 23 0 0.413323431 Non- Diabetic
## 576 0.280 25 0 0.227255560 Non- Diabetic
## 577 0.813 35 0 0.204597740 Non- Diabetic
## 578 0.693 21 1 0.473996890 Non- Diabetic
## 579 0.245 36 0 0.445599566 Non- Diabetic
## 580 0.575 62 1 0.840535897 Diabetic
## 581 0.371 21 1 0.579574846 Non- Diabetic
## 582 0.206 27 0 0.143235332 Non- Diabetic
## 583 0.259 62 0 0.413625704 Non- Diabetic
## 584 0.190 42 0 0.346810281 Non- Diabetic
## 585 0.687 52 1 0.436045608 Non- Diabetic
## 586 0.417 22 0 0.044781041 Non- Diabetic
## 587 0.129 41 1 0.595806910 Non- Diabetic
## 588 0.249 29 0 0.118651529 Non- Diabetic
## 589 1.154 52 1 0.821568127 Diabetic
## 590 0.342 25 0 0.017206912 Non- Diabetic
## 591 0.925 45 1 0.820498568 Diabetic
## 592 0.175 24 0 0.255818340 Non- Diabetic
## 593 0.402 44 1 0.379137491 Non- Diabetic
## 594 1.699 25 0 0.167965963 Non- Diabetic
## 595 0.733 34 0 0.470154078 Non- Diabetic
## 596 0.682 22 1 0.719869014 Diabetic
## 597 0.194 46 0 0.090866940 Non- Diabetic
## 598 0.559 21 0 0.068598096 Non- Diabetic
## 599 0.088 38 1 0.616288358 Diabetic
## 600 0.407 26 0 0.076115604 Non- Diabetic
## 601 0.400 24 0 0.100392196 Non- Diabetic
## 602 0.190 28 0 0.088012365 Non- Diabetic
## 603 0.100 30 0 0.132066134 Non- Diabetic
## 604 0.692 54 1 0.732189113 Diabetic
## 605 0.212 36 1 0.652268772 Diabetic
## 606 0.514 21 0 0.305009050 Non- Diabetic
## 607 1.258 22 1 0.887635425 Diabetic
## 608 0.482 25 0 0.035890116 Non- Diabetic
## 609 0.270 27 0 0.552531712 Non- Diabetic
## 610 0.138 23 0 0.069303835 Non- Diabetic
## 611 0.292 24 0 0.149344427 Non- Diabetic
## 612 0.593 36 1 0.715068029 Diabetic
## 613 0.787 40 1 0.873821411 Diabetic
## 614 0.878 26 0 0.338671455 Non- Diabetic
## 615 0.557 50 1 0.759697280 Diabetic
## 616 0.207 27 0 0.095075479 Non- Diabetic
## 617 0.157 30 0 0.221743316 Non- Diabetic
## 618 0.257 23 0 0.016629527 Non- Diabetic
## 619 1.282 50 1 0.498104870 Non- Diabetic
## 620 0.141 24 1 0.146749911 Non- Diabetic
## 621 0.246 28 0 0.251770690 Non- Diabetic
## 622 1.698 28 0 0.162038620 Non- Diabetic
## 623 1.461 45 0 0.957341896 Diabetic
## 624 0.347 21 0 0.191742938 Non- Diabetic
## 625 0.158 21 0 0.124585948 Non- Diabetic
## 626 0.362 29 0 0.186863632 Non- Diabetic
## 627 0.206 21 0 0.102932948 Non- Diabetic
## 628 0.393 21 0 0.248122820 Non- Diabetic
## 629 0.144 45 0 0.366071664 Non- Diabetic
## 630 0.148 21 0 0.066206969 Non- Diabetic
## 631 0.732 34 1 0.310216183 Non- Diabetic
## 632 0.238 24 0 0.114362643 Non- Diabetic
## 633 0.343 23 0 0.111221999 Non- Diabetic
## 634 0.115 22 0 0.146221912 Non- Diabetic
## 635 0.167 31 0 0.151929608 Non- Diabetic
## 636 0.465 38 1 0.457827391 Non- Diabetic
## 637 0.153 48 0 0.139471146 Non- Diabetic
## 638 0.649 23 0 0.130856127 Non- Diabetic
## 639 0.871 32 1 0.482025417 Non- Diabetic
## 640 0.149 28 0 0.034516079 Non- Diabetic
## 641 0.695 27 0 0.111188911 Non- Diabetic
## 642 0.303 24 0 0.359777448 Non- Diabetic
## 643 0.178 50 1 0.452584797 Non- Diabetic
## 644 0.610 31 0 0.111404377 Non- Diabetic
## 645 0.730 27 0 0.151381123 Non- Diabetic
## 646 0.134 30 0 0.589486261 Non- Diabetic
## 647 0.447 33 1 0.367257625 Non- Diabetic
## 648 0.455 22 1 0.719420396 Diabetic
## 649 0.260 42 1 0.537312590 Non- Diabetic
## 650 0.133 23 0 0.064629619 Non- Diabetic
## 651 0.234 23 0 0.044797662 Non- Diabetic
## 652 0.466 27 0 0.219886295 Non- Diabetic
## 653 0.269 28 0 0.344837994 Non- Diabetic
## 654 0.455 27 0 0.163515195 Non- Diabetic
## 655 0.142 22 0 0.131964085 Non- Diabetic
## 656 0.240 25 1 0.582396318 Non- Diabetic
## 657 0.155 22 0 0.049691979 Non- Diabetic
## 658 1.162 41 0 0.474413225 Non- Diabetic
## 659 0.190 51 0 0.670123038 Diabetic
## 660 1.292 27 1 0.197786638 Non- Diabetic
## 661 0.182 54 0 0.674739577 Diabetic
## 662 1.394 22 1 0.953680221 Diabetic
## 663 0.165 43 1 0.807517989 Diabetic
## 664 0.637 40 1 0.788328984 Diabetic
## 665 0.245 40 1 0.307221303 Non- Diabetic
## 666 0.217 24 0 0.172367851 Non- Diabetic
## 667 0.235 70 1 0.440826345 Non- Diabetic
## 668 0.141 40 1 0.271541111 Non- Diabetic
## 669 0.430 43 0 0.236092069 Non- Diabetic
## 670 0.164 45 0 0.641344392 Diabetic
## 671 0.631 49 0 0.760818670 Diabetic
## 672 0.551 21 0 0.076198871 Non- Diabetic
## 673 0.285 47 0 0.171739521 Non- Diabetic
## 674 0.880 22 0 0.832851470 Diabetic
## 675 0.587 68 0 0.303078552 Non- Diabetic
## 676 0.328 31 1 0.836144232 Diabetic
## 677 0.230 53 1 0.545859569 Non- Diabetic
## 678 0.263 25 0 0.095419232 Non- Diabetic
## 679 0.127 25 1 0.276168740 Non- Diabetic
## 680 0.614 23 0 0.088642638 Non- Diabetic
## 681 0.332 22 0 0.017087852 Non- Diabetic
## 682 0.364 26 1 0.788383202 Diabetic
## 683 0.366 22 0 0.215043546 Non- Diabetic
## 684 0.536 27 1 0.346480580 Non- Diabetic
## 685 0.640 69 0 0.057252428 Non- Diabetic
## 686 0.591 25 0 0.338918511 Non- Diabetic
## 687 0.314 22 0 0.167250673 Non- Diabetic
## 688 0.181 29 0 0.089410834 Non- Diabetic
## 689 0.828 23 0 0.265125614 Non- Diabetic
## 690 0.335 46 1 0.633684832 Diabetic
## 691 0.856 34 0 0.267096010 Non- Diabetic
## 692 0.257 44 1 0.913170501 Diabetic
## 693 0.886 23 0 0.460827693 Non- Diabetic
## 694 0.439 43 1 0.592640671 Non- Diabetic
## 695 0.191 25 0 0.041830342 Non- Diabetic
## 696 0.128 43 1 0.456106565 Non- Diabetic
## 697 0.268 31 1 0.551414384 Non- Diabetic
## 698 0.253 22 0 0.050005967 Non- Diabetic
## 699 0.598 28 0 0.419466816 Non- DiabeticObservation
Thus, the test data has been tested for Outcome prediction, as above.
Test Data Confusion Matrix
resVal <- predict(mgmModel,dfrTest, type='response')
prdSur <- ifelse(resVal > 0.6,1, 0)
cnfmtrx <- table(prd=prdSur, act=dfrTest$Outcome)
confusionMatrix(cnfmtrx)## Confusion Matrix and Statistics
##
## act
## prd 0 1
## 0 426 128
## 1 32 113
##
## Accuracy : 0.7711
## 95% CI : (0.7381, 0.8018)
## No Information Rate : 0.6552
## P-Value [Acc > NIR] : 1.790e-11
##
## Kappa : 0.4406
## Mcnemar's Test P-Value : 5.894e-14
##
## Sensitivity : 0.9301
## Specificity : 0.4689
## Pos Pred Value : 0.7690
## Neg Pred Value : 0.7793
## Prevalence : 0.6552
## Detection Rate : 0.6094
## Detection Prevalence : 0.7926
## Balanced Accuracy : 0.6995
##
## 'Positive' Class : 0
## Observation
There is an accuracy of more than 77 % of the actual outcome in the predicted outcome.