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##### Chapter 5: Classification using Decision Trees and Rules -------------------
#### Part 1: Decision Trees -------------------
## Understanding Decision Trees ----
# calculate entropy of a two-class segment
-0.60 * log2(0.60) - 0.40 * log2(0.40)## [1] 0.9709506curve(-x * log2(x) - (1 - x) * log2(1 - x),
col = "red", xlab = "x", ylab = "Entropy", lwd = 4)
## Example: Identifying Risky Bank Loans ----
## Step 2: Exploring and preparing the data ----
credit <- read.csv("credit.csv")
str(credit)## 'data.frame': 1000 obs. of 17 variables:
## $ checking_balance : Factor w/ 4 levels "< 0 DM","> 200 DM",..: 1 3 4 1 1 4 4 3 4 3 ...
## $ months_loan_duration: int 6 48 12 42 24 36 24 36 12 30 ...
## $ credit_history : Factor w/ 5 levels "critical","good",..: 1 2 1 2 4 2 2 2 2 1 ...
## $ purpose : Factor w/ 6 levels "business","car",..: 5 5 4 5 2 4 5 2 5 2 ...
## $ amount : int 1169 5951 2096 7882 4870 9055 2835 6948 3059 5234 ...
## $ savings_balance : Factor w/ 5 levels "< 100 DM","> 1000 DM",..: 5 1 1 1 1 5 4 1 2 1 ...
## $ employment_duration : Factor w/ 5 levels "< 1 year","> 7 years",..: 2 3 4 4 3 3 2 3 4 5 ...
## $ percent_of_income : int 4 2 2 2 3 2 3 2 2 4 ...
## $ years_at_residence : int 4 2 3 4 4 4 4 2 4 2 ...
## $ age : int 67 22 49 45 53 35 53 35 61 28 ...
## $ other_credit : Factor w/ 3 levels "bank","none",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ housing : Factor w/ 3 levels "other","own",..: 2 2 2 1 1 1 2 3 2 2 ...
## $ existing_loans_count: int 2 1 1 1 2 1 1 1 1 2 ...
## $ job : Factor w/ 4 levels "management","skilled",..: 2 2 4 2 2 4 2 1 4 1 ...
## $ dependents : int 1 1 2 2 2 2 1 1 1 1 ...
## $ phone : Factor w/ 2 levels "no","yes": 2 1 1 1 1 2 1 2 1 1 ...
## $ default : Factor w/ 2 levels "no","yes": 1 2 1 1 2 1 1 1 1 2 ...# look at two characteristics of the applicant
table(credit$checking_balance)##
## < 0 DM > 200 DM 1 - 200 DM unknown
## 274 63 269 394table(credit$savings_balance)##
## < 100 DM > 1000 DM 100 - 500 DM 500 - 1000 DM unknown
## 603 48 103 63 183# look at two characteristics of the loan
summary(credit$months_loan_duration)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.0 12.0 18.0 20.9 24.0 72.0summary(credit$amount)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 250 1366 2320 3271 3972 18420# look at the class variable
table(credit$default)##
## no yes
## 700 300# create a random sample for training and test data
# use set.seed to use the same random number sequence as the tutorial
set.seed(123)
train_sample <- sample(1000, 900)
str(train_sample)## int [1:900] 288 788 409 881 937 46 525 887 548 453 ...# split the data frames
credit_train <- credit[train_sample, ]
credit_test <- credit[-train_sample, ]
# check the proportion of class variable
prop.table(table(credit_train$default))##
## no yes
## 0.7033333 0.2966667prop.table(table(credit_test$default))##
## no yes
## 0.67 0.33## Step 3: Training a model on the data ----
# build the simplest decision tree
library(C50)## Warning: package 'C50' was built under R version 3.3.3
credit_model <- C5.0(credit_train[-17], credit_train$default)
# display simple facts about the tree
credit_model##
## Call:
## C5.0.default(x = credit_train[-17], y = credit_train$default)
##
## Classification Tree
## Number of samples: 900
## Number of predictors: 16
##
## Tree size: 57
##
## Non-standard options: attempt to group attributes# display detailed information about the tree
summary(credit_model)##
## Call:
## C5.0.default(x = credit_train[-17], y = credit_train$default)
##
##
## C5.0 [Release 2.07 GPL Edition] Sun Apr 30 19:56:15 2017
## -------------------------------
##
## Class specified by attribute `outcome'
##
## Read 900 cases (17 attributes) from undefined.data
##
## Decision tree:
##
## checking_balance in {> 200 DM,unknown}: no (412/50)
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...credit_history in {perfect,very good}: yes (59/18)
## credit_history in {critical,good,poor}:
## :...months_loan_duration <= 22:
## :...credit_history = critical: no (72/14)
## : credit_history = poor:
## : :...dependents > 1: no (5)
## : : dependents <= 1:
## : : :...years_at_residence <= 3: yes (4/1)
## : : years_at_residence > 3: no (5/1)
## : credit_history = good:
## : :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (15/1)
## : savings_balance = 100 - 500 DM:
## : :...other_credit = bank: yes (3)
## : : other_credit in {none,store}: no (9/2)
## : savings_balance = unknown:
## : :...other_credit = bank: yes (1)
## : : other_credit in {none,store}: no (21/8)
## : savings_balance = < 100 DM:
## : :...purpose in {business,car0,renovations}: no (8/2)
## : purpose = education:
## : :...checking_balance = < 0 DM: yes (4)
## : : checking_balance = 1 - 200 DM: no (1)
## : purpose = car:
## : :...employment_duration = > 7 years: yes (5)
## : : employment_duration = unemployed: no (4/1)
## : : employment_duration = < 1 year:
## : : :...years_at_residence <= 2: yes (5)
## : : : years_at_residence > 2: no (3/1)
## : : employment_duration = 1 - 4 years:
## : : :...years_at_residence <= 2: yes (2)
## : : : years_at_residence > 2: no (6/1)
## : : employment_duration = 4 - 7 years:
## : : :...amount <= 1680: yes (2)
## : : amount > 1680: no (3)
## : purpose = furniture/appliances:
## : :...job in {management,unskilled}: no (23/3)
## : job = unemployed: yes (1)
## : job = skilled:
## : :...months_loan_duration > 13: [S1]
## : months_loan_duration <= 13:
## : :...housing in {other,own}: no (23/4)
## : housing = rent:
## : :...percent_of_income <= 3: yes (3)
## : percent_of_income > 3: no (2)
## months_loan_duration > 22:
## :...savings_balance = > 1000 DM: no (2)
## savings_balance = 500 - 1000 DM: yes (4/1)
## savings_balance = 100 - 500 DM:
## :...credit_history in {critical,poor}: no (14/3)
## : credit_history = good:
## : :...other_credit = bank: no (1)
## : other_credit in {none,store}: yes (12/2)
## savings_balance = unknown:
## :...checking_balance = 1 - 200 DM: no (17)
## : checking_balance = < 0 DM:
## : :...credit_history = critical: no (1)
## : credit_history in {good,poor}: yes (12/3)
## savings_balance = < 100 DM:
## :...months_loan_duration > 47: yes (21/2)
## months_loan_duration <= 47:
## :...housing = other:
## :...percent_of_income <= 2: no (6)
## : percent_of_income > 2: yes (9/3)
## housing = rent:
## :...other_credit = bank: no (1)
## : other_credit in {none,store}: yes (16/3)
## housing = own:
## :...employment_duration = > 7 years: no (13/4)
## employment_duration = 4 - 7 years:
## :...job in {management,skilled,
## : : unemployed}: yes (9/1)
## : job = unskilled: no (1)
## employment_duration = unemployed:
## :...years_at_residence <= 2: yes (4)
## : years_at_residence > 2: no (3)
## employment_duration = 1 - 4 years:
## :...purpose in {business,car0,education}: yes (7/1)
## : purpose in {furniture/appliances,
## : : renovations}: no (7)
## : purpose = car:
## : :...years_at_residence <= 3: yes (3)
## : years_at_residence > 3: no (3)
## employment_duration = < 1 year:
## :...years_at_residence > 3: yes (5)
## years_at_residence <= 3:
## :...other_credit = bank: no (0)
## other_credit = store: yes (1)
## other_credit = none:
## :...checking_balance = 1 - 200 DM: no (8/2)
## checking_balance = < 0 DM:
## :...job in {management,skilled,
## : unemployed}: yes (2)
## job = unskilled: no (3/1)
##
## SubTree [S1]
##
## employment_duration in {< 1 year,4 - 7 years}: no (4)
## employment_duration in {> 7 years,1 - 4 years,unemployed}: yes (10)
##
##
## Evaluation on training data (900 cases):
##
## Decision Tree
## ----------------
## Size Errors
##
## 56 133(14.8%) <<
##
##
## (a) (b) <-classified as
## ---- ----
## 598 35 (a): class no
## 98 169 (b): class yes
##
##
## Attribute usage:
##
## 100.00% checking_balance
## 54.22% credit_history
## 47.67% months_loan_duration
## 38.11% savings_balance
## 14.33% purpose
## 14.33% housing
## 12.56% employment_duration
## 9.00% job
## 8.67% other_credit
## 6.33% years_at_residence
## 2.22% percent_of_income
## 1.56% dependents
## 0.56% amount
##
##
## Time: 0.0 secs## Step 4: Evaluating model performance ----
# create a factor vector of predictions on test data
credit_pred <- predict(credit_model, credit_test)
# cross tabulation of predicted versus actual classes
library(gmodels)## Warning: package 'gmodels' was built under R version 3.3.3CrossTable(credit_test$default, credit_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 100
##
##
## | predicted default
## actual default | no | yes | Row Total |
## ---------------|-----------|-----------|-----------|
## no | 59 | 8 | 67 |
## | 0.590 | 0.080 | |
## ---------------|-----------|-----------|-----------|
## yes | 19 | 14 | 33 |
## | 0.190 | 0.140 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 78 | 22 | 100 |
## ---------------|-----------|-----------|-----------|
##
## ## Step 5: Improving model performance ----
## Boosting the accuracy of decision trees
# boosted decision tree with 10 trials
credit_boost10 <- C5.0(credit_train[-17], credit_train$default,
trials = 10)
credit_boost10##
## Call:
## C5.0.default(x = credit_train[-17], y = credit_train$default, trials = 10)
##
## Classification Tree
## Number of samples: 900
## Number of predictors: 16
##
## Number of boosting iterations: 10
## Average tree size: 47.5
##
## Non-standard options: attempt to group attributessummary(credit_boost10)##
## Call:
## C5.0.default(x = credit_train[-17], y = credit_train$default, trials = 10)
##
##
## C5.0 [Release 2.07 GPL Edition] Sun Apr 30 19:56:15 2017
## -------------------------------
##
## Class specified by attribute `outcome'
##
## Read 900 cases (17 attributes) from undefined.data
##
## ----- Trial 0: -----
##
## Decision tree:
##
## checking_balance in {> 200 DM,unknown}: no (412/50)
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...credit_history in {perfect,very good}: yes (59/18)
## credit_history in {critical,good,poor}:
## :...months_loan_duration <= 22:
## :...credit_history = critical: no (72/14)
## : credit_history = poor:
## : :...dependents > 1: no (5)
## : : dependents <= 1:
## : : :...years_at_residence <= 3: yes (4/1)
## : : years_at_residence > 3: no (5/1)
## : credit_history = good:
## : :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (15/1)
## : savings_balance = 100 - 500 DM:
## : :...other_credit = bank: yes (3)
## : : other_credit in {none,store}: no (9/2)
## : savings_balance = unknown:
## : :...other_credit = bank: yes (1)
## : : other_credit in {none,store}: no (21/8)
## : savings_balance = < 100 DM:
## : :...purpose in {business,car0,renovations}: no (8/2)
## : purpose = education:
## : :...checking_balance = < 0 DM: yes (4)
## : : checking_balance = 1 - 200 DM: no (1)
## : purpose = car:
## : :...employment_duration = > 7 years: yes (5)
## : : employment_duration = unemployed: no (4/1)
## : : employment_duration = < 1 year:
## : : :...years_at_residence <= 2: yes (5)
## : : : years_at_residence > 2: no (3/1)
## : : employment_duration = 1 - 4 years:
## : : :...years_at_residence <= 2: yes (2)
## : : : years_at_residence > 2: no (6/1)
## : : employment_duration = 4 - 7 years:
## : : :...amount <= 1680: yes (2)
## : : amount > 1680: no (3)
## : purpose = furniture/appliances:
## : :...job in {management,unskilled}: no (23/3)
## : job = unemployed: yes (1)
## : job = skilled:
## : :...months_loan_duration > 13: [S1]
## : months_loan_duration <= 13:
## : :...housing in {other,own}: no (23/4)
## : housing = rent:
## : :...percent_of_income <= 3: yes (3)
## : percent_of_income > 3: no (2)
## months_loan_duration > 22:
## :...savings_balance = > 1000 DM: no (2)
## savings_balance = 500 - 1000 DM: yes (4/1)
## savings_balance = 100 - 500 DM:
## :...credit_history in {critical,poor}: no (14/3)
## : credit_history = good:
## : :...other_credit = bank: no (1)
## : other_credit in {none,store}: yes (12/2)
## savings_balance = unknown:
## :...checking_balance = 1 - 200 DM: no (17)
## : checking_balance = < 0 DM:
## : :...credit_history = critical: no (1)
## : credit_history in {good,poor}: yes (12/3)
## savings_balance = < 100 DM:
## :...months_loan_duration > 47: yes (21/2)
## months_loan_duration <= 47:
## :...housing = other:
## :...percent_of_income <= 2: no (6)
## : percent_of_income > 2: yes (9/3)
## housing = rent:
## :...other_credit = bank: no (1)
## : other_credit in {none,store}: yes (16/3)
## housing = own:
## :...employment_duration = > 7 years: no (13/4)
## employment_duration = 4 - 7 years:
## :...job in {management,skilled,
## : : unemployed}: yes (9/1)
## : job = unskilled: no (1)
## employment_duration = unemployed:
## :...years_at_residence <= 2: yes (4)
## : years_at_residence > 2: no (3)
## employment_duration = 1 - 4 years:
## :...purpose in {business,car0,education}: yes (7/1)
## : purpose in {furniture/appliances,
## : : renovations}: no (7)
## : purpose = car:
## : :...years_at_residence <= 3: yes (3)
## : years_at_residence > 3: no (3)
## employment_duration = < 1 year:
## :...years_at_residence > 3: yes (5)
## years_at_residence <= 3:
## :...other_credit = bank: no (0)
## other_credit = store: yes (1)
## other_credit = none:
## :...checking_balance = 1 - 200 DM: no (8/2)
## checking_balance = < 0 DM:
## :...job in {management,skilled,
## : unemployed}: yes (2)
## job = unskilled: no (3/1)
##
## SubTree [S1]
##
## employment_duration in {< 1 year,4 - 7 years}: no (4)
## employment_duration in {> 7 years,1 - 4 years,unemployed}: yes (10)
##
## ----- Trial 1: -----
##
## Decision tree:
##
## checking_balance = unknown:
## :...other_credit in {bank,store}:
## : :...purpose in {business,education,renovations}: yes (19.5/6.3)
## : : purpose in {car0,furniture/appliances}: no (24.8/6.6)
## : : purpose = car:
## : : :...dependents <= 1: yes (20.1/4.8)
## : : dependents > 1: no (2.4)
## : other_credit = none:
## : :...credit_history in {critical,perfect,very good}: no (102.8/4.4)
## : credit_history = good:
## : :...existing_loans_count <= 1: no (112.7/17.5)
## : : existing_loans_count > 1: yes (18.9/7.9)
## : credit_history = poor:
## : :...years_at_residence <= 1: yes (4.4)
## : years_at_residence > 1:
## : :...percent_of_income <= 3: no (11.9)
## : percent_of_income > 3: yes (14.3/5.6)
## checking_balance in {< 0 DM,> 200 DM,1 - 200 DM}:
## :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (42.9/11.3)
## savings_balance = unknown:
## :...credit_history in {perfect,poor}: no (8.5)
## : credit_history in {critical,good,very good}:
## : :...employment_duration in {< 1 year,> 7 years,4 - 7 years,
## : : unemployed}: no (52.3/17.3)
## : employment_duration = 1 - 4 years: yes (19.7/5.6)
## savings_balance = 100 - 500 DM:
## :...existing_loans_count > 3: yes (3)
## : existing_loans_count <= 3:
## : :...credit_history in {critical,poor,very good}: no (24.6/7.6)
## : credit_history = perfect: yes (2.4)
## : credit_history = good:
## : :...months_loan_duration <= 27: no (23.7/10.5)
## : months_loan_duration > 27: yes (5.6)
## savings_balance = < 100 DM:
## :...months_loan_duration > 42: yes (28/5.2)
## months_loan_duration <= 42:
## :...percent_of_income <= 2:
## :...employment_duration in {1 - 4 years,4 - 7 years,
## : : unemployed}: no (86.2/23.8)
## : employment_duration in {< 1 year,> 7 years}:
## : :...housing = other: no (4.8/1.6)
## : housing = rent: yes (10.7/2.4)
## : housing = own:
## : :...phone = yes: yes (12.9/4)
## : phone = no:
## : :...percent_of_income <= 1: no (7.1/0.8)
## : percent_of_income > 1: yes (17.5/7.1)
## percent_of_income > 2:
## :...years_at_residence <= 1: no (31.6/8.5)
## years_at_residence > 1:
## :...credit_history in {perfect,poor}: yes (20.9/1.6)
## credit_history in {critical,good,very good}:
## :...job = skilled: yes (95/34.7)
## job = unemployed: no (1.6)
## job = management:
## :...amount <= 11590: no (23.8/7)
## : amount > 11590: yes (3.8)
## job = unskilled:
## :...checking_balance in {< 0 DM,
## : > 200 DM}: yes (23.8/9.5)
## checking_balance = 1 - 200 DM: no (17.9/6.2)
##
## ----- Trial 2: -----
##
## Decision tree:
##
## checking_balance = unknown:
## :...other_credit = bank:
## : :...existing_loans_count > 2: no (3.3)
## : : existing_loans_count <= 2:
## : : :...months_loan_duration <= 8: no (4)
## : : months_loan_duration > 8: yes (43/16.6)
## : other_credit in {none,store}:
## : :...employment_duration in {< 1 year,unemployed}:
## : :...purpose in {business,renovations}: yes (6.4)
## : : purpose in {car,car0,education}: no (13.2)
## : : purpose = furniture/appliances:
## : : :...amount <= 4594: no (22.5/7.3)
## : : amount > 4594: yes (9.1)
## : employment_duration in {> 7 years,1 - 4 years,4 - 7 years}:
## : :...percent_of_income <= 3: no (92.7/3.6)
## : percent_of_income > 3:
## : :...age > 30: no (73.6/5.5)
## : age <= 30:
## : :...job in {management,unemployed,unskilled}: yes (14/4)
## : job = skilled:
## : :...credit_history = very good: no (0)
## : credit_history = poor: yes (3.6)
## : credit_history in {critical,good,perfect}:
## : :...age <= 29: no (20.4/4.6)
## : age > 29: yes (2.7)
## checking_balance in {< 0 DM,> 200 DM,1 - 200 DM}:
## :...housing = other:
## :...dependents > 1: yes (28.3/7.6)
## : dependents <= 1:
## : :...employment_duration in {< 1 year,4 - 7 years,
## : : unemployed}: no (22.9/4.5)
## : employment_duration in {> 7 years,1 - 4 years}: yes (29.6/10.5)
## housing = rent:
## :...credit_history = perfect: yes (5.3)
## : credit_history = poor: no (7.1/0.7)
## : credit_history in {critical,good,very good}:
## : :...employment_duration = < 1 year: yes (28.3/9.3)
## : employment_duration in {> 7 years,4 - 7 years,
## : : unemployed}: no (33.9/12.3)
## : employment_duration = 1 - 4 years:
## : :...checking_balance = > 200 DM: no (2)
## : checking_balance in {< 0 DM,1 - 200 DM}:
## : :...years_at_residence <= 3: no (10.3/3.8)
## : years_at_residence > 3: yes (20.4/3.1)
## housing = own:
## :...job in {management,unemployed}: yes (55.8/19.8)
## job in {skilled,unskilled}:
## :...months_loan_duration <= 7: no (25.3/2)
## months_loan_duration > 7:
## :...years_at_residence > 3: no (92.2/29.6)
## years_at_residence <= 3:
## :...purpose = renovations: yes (7/1.3)
## purpose in {business,car0,education}: no (32.2/5.3)
## purpose = car:
## :...months_loan_duration > 40: no (7.2/0.7)
## : months_loan_duration <= 40:
## : :...amount <= 947: yes (12.9)
## : amount > 947:
## : :...months_loan_duration <= 16: no (23.2/8.5)
## : months_loan_duration > 16: [S1]
## purpose = furniture/appliances:
## :...savings_balance in {> 1000 DM,unknown}: no (15.4/3.2)
## savings_balance in {100 - 500 DM,
## : 500 - 1000 DM}: yes (14.6/4.5)
## savings_balance = < 100 DM:
## :...months_loan_duration > 36: yes (7.1)
## months_loan_duration <= 36:
## :...existing_loans_count > 1: no (14.1/4.3)
## existing_loans_count <= 1: [S2]
##
## SubTree [S1]
##
## savings_balance in {< 100 DM,> 1000 DM,500 - 1000 DM,unknown}: yes (22.5/2.7)
## savings_balance = 100 - 500 DM: no (4.5/0.7)
##
## SubTree [S2]
##
## checking_balance = < 0 DM: no (22.4/9.1)
## checking_balance in {> 200 DM,1 - 200 DM}: yes (46.7/20)
##
## ----- Trial 3: -----
##
## Decision tree:
##
## checking_balance in {> 200 DM,unknown}:
## :...employment_duration = > 7 years: no (98.9/17.1)
## : employment_duration = unemployed: yes (16/6.7)
## : employment_duration = < 1 year:
## : :...amount <= 1333: no (11.7)
## : : amount > 1333:
## : : :...amount <= 6681: no (38.2/16.3)
## : : amount > 6681: yes (5.3)
## : employment_duration = 4 - 7 years:
## : :...checking_balance = > 200 DM: yes (9.6/3.6)
## : : checking_balance = unknown:
## : : :...age <= 22: yes (6.5/1.6)
## : : age > 22: no (42.6/1.5)
## : employment_duration = 1 - 4 years:
## : :...percent_of_income <= 1: no (20.6/1.5)
## : percent_of_income > 1:
## : :...job in {skilled,unemployed}: no (64.9/17.6)
## : job in {management,unskilled}:
## : :...existing_loans_count > 2: yes (2.4)
## : existing_loans_count <= 2:
## : :...age <= 34: yes (26.4/10.7)
## : age > 34: no (10.5)
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (35.8/12)
## savings_balance = 100 - 500 DM:
## :...amount <= 1285: yes (12.8/0.5)
## : amount > 1285:
## : :...existing_loans_count <= 1: no (27/9.2)
## : existing_loans_count > 1: yes (15.8/4.9)
## savings_balance = unknown:
## :...credit_history in {critical,perfect,poor}: no (15.5)
## : credit_history in {good,very good}:
## : :...age > 56: no (4.5)
## : age <= 56:
## : :...months_loan_duration <= 18: yes (24.5/5.6)
## : months_loan_duration > 18: no (28.4/12.3)
## savings_balance = < 100 DM:
## :...months_loan_duration <= 11:
## :...job = management: yes (13.7/4.9)
## : job in {skilled,unemployed,unskilled}: no (45.9/10)
## months_loan_duration > 11:
## :...percent_of_income <= 1:
## :...credit_history in {critical,poor,very good}: no (11.1)
## : credit_history in {good,perfect}: yes (24.4/11)
## percent_of_income > 1:
## :...job = unemployed: yes (7/3.1)
## job = management:
## :...years_at_residence <= 1: no (6.6)
## : years_at_residence > 1:
## : :...checking_balance = < 0 DM: no (23.1/7)
## : checking_balance = 1 - 200 DM: yes (15.8/4)
## job = unskilled:
## :...housing in {other,rent}: yes (12.2/2.2)
## : housing = own:
## : :...purpose = car: yes (18.1/3.9)
## : purpose in {business,car0,education,
## : furniture/appliances,
## : renovations}: no (32.1/11.1)
## job = skilled:
## :...checking_balance = < 0 DM:
## :...credit_history in {poor,very good}: yes (16.6)
## : credit_history in {critical,good,perfect}:
## : :...purpose in {business,car0,education,
## : : renovations}: yes (10.2/1.5)
## : purpose = car:
## : :...age <= 51: yes (34.6/8.1)
## : : age > 51: no (4.4)
## : purpose = furniture/appliances:
## : :...years_at_residence <= 1: no (4.4)
## : years_at_residence > 1:
## : :...other_credit = bank: yes (2.4)
## : other_credit = store: no (0.5)
## : other_credit = none:
## : :...amount <= 1743: no (11.5/2.4)
## : amount > 1743: yes (29/6.6)
## checking_balance = 1 - 200 DM:
## :...months_loan_duration > 36: yes (6.5)
## months_loan_duration <= 36:
## :...other_credit in {bank,store}: yes (8/1.5)
## other_credit = none:
## :...dependents > 1: yes (7.4/3.1)
## dependents <= 1:
## :...percent_of_income <= 2: no (12.7/1.1)
## percent_of_income > 2: [S1]
##
## SubTree [S1]
##
## purpose in {business,renovations}: yes (3.9)
## purpose in {car,car0,education,furniture/appliances}: no (19.8/6.1)
##
## ----- Trial 4: -----
##
## Decision tree:
##
## checking_balance in {> 200 DM,unknown}:
## :...other_credit = store: no (20.6/9.6)
## : other_credit = none:
## : :...employment_duration in {> 7 years,1 - 4 years,4 - 7 years,
## : : : unemployed}: no (211.3/45.7)
## : : employment_duration = < 1 year:
## : : :...amount <= 1333: no (8.8)
## : : amount > 1333:
## : : :...purpose in {business,car0,education,furniture/appliances,
## : : : renovations}: yes (32.9/8.1)
## : : purpose = car: no (4.9)
## : other_credit = bank:
## : :...age > 44: no (14.4/1.2)
## : age <= 44:
## : :...years_at_residence <= 1: no (5)
## : years_at_residence > 1:
## : :...housing = rent: yes (4.3)
## : housing in {other,own}:
## : :...job = unemployed: yes (0)
## : job = management: no (4)
## : job in {skilled,unskilled}:
## : :...age <= 26: no (3.7)
## : age > 26:
## : :...savings_balance in {< 100 DM,500 - 1000 DM,
## : : unknown}: yes (30.6/7.4)
## : savings_balance in {> 1000 DM,
## : 100 - 500 DM}: no (4)
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...credit_history = perfect:
## :...housing in {other,rent}: yes (7.8)
## : housing = own: no (20.5/9)
## credit_history = poor:
## :...checking_balance = < 0 DM: yes (10.4/2.2)
## : checking_balance = 1 - 200 DM:
## : :...other_credit in {bank,none}: no (24/4.3)
## : other_credit = store: yes (5.8/1.2)
## credit_history = very good:
## :...age <= 23: no (5.7)
## : age > 23:
## : :...months_loan_duration <= 27: yes (28.4/3.7)
## : months_loan_duration > 27: no (6.9/2)
## credit_history = critical:
## :...years_at_residence <= 1: no (6.7)
## : years_at_residence > 1:
## : :...purpose in {business,car,car0,renovations}: no (62.2/21.9)
## : purpose = education: yes (7.9/0.9)
## : purpose = furniture/appliances:
## : :...phone = yes: no (14.5/2.8)
## : phone = no:
## : :...amount <= 1175: no (5.2)
## : amount > 1175: yes (30.1/7.6)
## credit_history = good:
## :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (15.7/4.7)
## savings_balance = 100 - 500 DM: yes (32.1/11.7)
## savings_balance = unknown:
## :...job = unskilled: no (4.4)
## : job in {management,skilled,unemployed}:
## : :...checking_balance = < 0 DM: yes (27.8/6)
## : checking_balance = 1 - 200 DM: no (26.8/10.4)
## savings_balance = < 100 DM:
## :...dependents > 1:
## :...existing_loans_count > 1: no (2.6/0.4)
## : existing_loans_count <= 1:
## : :...years_at_residence <= 2: yes (10.2/2.9)
## : years_at_residence > 2: no (20.4/5.9)
## dependents <= 1:
## :...purpose in {business,car0}: no (9.7/2.5)
## purpose in {education,renovations}: yes (13/5.1)
## purpose = car:
## :...employment_duration in {< 1 year,> 7 years,
## : : 4 - 7 years}: yes (32/8.3)
## : employment_duration in {1 - 4 years,
## : unemployed}: no (24.9/9)
## purpose = furniture/appliances:
## :...months_loan_duration > 39: yes (4.8)
## months_loan_duration <= 39:
## :...phone = yes: yes (21.9/9.2)
## phone = no:
## :...employment_duration in {< 1 year,> 7 years,
## : 4 - 7 years}: no (34.1/8.1)
## employment_duration = unemployed: yes (3.3/0.4)
## employment_duration = 1 - 4 years:
## :...percent_of_income <= 1: yes (3.8)
## percent_of_income > 1:
## :...months_loan_duration > 21: no (4.9/0.4)
## months_loan_duration <= 21:
## :...years_at_residence <= 3: no (20.9/8.8)
## years_at_residence > 3: yes (5.8)
##
## ----- Trial 5: -----
##
## Decision tree:
##
## checking_balance = unknown:
## :...other_credit = store: yes (16.9/7.5)
## : other_credit = bank:
## : :...housing = other: no (8.3/1.8)
## : : housing = rent: yes (4.4/0.8)
## : : housing = own:
## : : :...phone = no: no (26.9/9.7)
## : : phone = yes: yes (12.1/5)
## : other_credit = none:
## : :...credit_history in {critical,perfect,very good}: no (60.4/5.1)
## : credit_history in {good,poor}:
## : :...purpose in {business,car,car0,education}: no (53.6/12.8)
## : purpose = renovations: yes (7.3/1.1)
## : purpose = furniture/appliances:
## : :...job = unemployed: no (0)
## : job in {management,unskilled}: yes (19.2/7)
## : job = skilled:
## : :...phone = yes: no (14.6/1.8)
## : phone = no:
## : :...age > 32: no (9.2)
## : age <= 32:
## : :...employment_duration = 1 - 4 years: no (4.1)
## : employment_duration in {< 1 year,> 7 years,
## : : 4 - 7 years,unemployed}:
## : :...savings_balance in {< 100 DM,
## : : 100 - 500 DM}: yes (20.5/3)
## : savings_balance in {> 1000 DM,500 - 1000 DM,
## : unknown}: no (3.4)
## checking_balance in {< 0 DM,> 200 DM,1 - 200 DM}:
## :...percent_of_income <= 2:
## :...amount > 11054: yes (14.2/1.2)
## : amount <= 11054:
## : :...other_credit = bank: no (32.3/9.7)
## : other_credit = store: yes (8.9/2.6)
## : other_credit = none:
## : :...purpose in {business,renovations}: yes (20.3/9.1)
## : purpose in {car0,education}: no (8.4/3.7)
## : purpose = car:
## : :...savings_balance in {< 100 DM,> 1000 DM,500 - 1000 DM,
## : : : unknown}: no (46.6/7.9)
## : : savings_balance = 100 - 500 DM: yes (13.8/3.3)
## : purpose = furniture/appliances:
## : :...employment_duration in {> 7 years,
## : : 4 - 7 years}: no (18.2/2.6)
## : employment_duration in {1 - 4 years,
## : : unemployed}: yes (50.8/19.5)
## : employment_duration = < 1 year:
## : :...job in {management,skilled,unemployed}: no (16.3/2.9)
## : job = unskilled: yes (6/1.6)
## percent_of_income > 2:
## :...years_at_residence <= 1:
## :...other_credit in {bank,store}: no (7.6)
## : other_credit = none:
## : :...months_loan_duration > 42: no (2.9)
## : months_loan_duration <= 42:
## : :...age <= 36: no (26.6/8.4)
## : age > 36: yes (5.3)
## years_at_residence > 1:
## :...job = unemployed: no (5.2)
## job in {management,skilled,unskilled}:
## :...credit_history = perfect: yes (10.9)
## credit_history in {critical,good,poor,very good}:
## :...employment_duration = < 1 year:
## :...checking_balance = > 200 DM: no (2.7)
## : checking_balance in {< 0 DM,1 - 200 DM}:
## : :...months_loan_duration > 21: yes (23.4/0.7)
## : months_loan_duration <= 21:
## : :...amount <= 1928: yes (18.4/4.4)
## : amount > 1928: no (4.5)
## employment_duration in {> 7 years,1 - 4 years,4 - 7 years,
## : unemployed}:
## :...months_loan_duration <= 11:
## :...age > 47: no (12.2)
## : age <= 47:
## : :...purpose in {business,car,car0,
## : : furniture/appliances,
## : : renovations}: no (25/9.2)
## : purpose = education: yes (3.5)
## months_loan_duration > 11:
## :...savings_balance in {> 1000 DM,100 - 500 DM}:
## :...age <= 58: no (22.7/3.4)
## : age > 58: yes (4.4)
## savings_balance in {< 100 DM,500 - 1000 DM,unknown}:
## :...years_at_residence <= 2: yes (76.1/22.8)
## years_at_residence > 2:
## :...purpose in {business,car0,
## : education}: yes (24.7/7.1)
## purpose = renovations: no (1.1)
## purpose = furniture/appliances: [S1]
## purpose = car:
## :...amount <= 1388: yes (17.8/2.2)
## amount > 1388:
## :...housing = own: no (10.9)
## housing in {other,rent}: [S2]
##
## SubTree [S1]
##
## employment_duration = unemployed: no (4.4)
## employment_duration in {> 7 years,1 - 4 years,4 - 7 years}:
## :...checking_balance = < 0 DM: yes (35.6/12.4)
## checking_balance in {> 200 DM,1 - 200 DM}: no (29/10.5)
##
## SubTree [S2]
##
## savings_balance in {< 100 DM,500 - 1000 DM}: yes (21.4/6.4)
## savings_balance = unknown: no (6.8/1.5)
##
## ----- Trial 6: -----
##
## Decision tree:
##
## checking_balance in {> 200 DM,unknown}:
## :...purpose = car0: no (2.2)
## : purpose = renovations: yes (8.4/3.3)
## : purpose = education:
## : :...age <= 44: yes (19.8/7.7)
## : : age > 44: no (4.4)
## : purpose = business:
## : :...existing_loans_count > 2: yes (3.3)
## : : existing_loans_count <= 2:
## : : :...amount <= 1823: no (8.1)
## : : amount > 1823:
## : : :...percent_of_income <= 3: no (12.1/3.3)
## : : percent_of_income > 3: yes (13.2/3.4)
## : purpose = car:
## : :...job in {management,unemployed}: no (20.8/1.6)
## : : job = unskilled:
## : : :...years_at_residence <= 3: no (11/1.3)
## : : : years_at_residence > 3: yes (14.5/3.2)
## : : job = skilled:
## : : :...other_credit in {bank,store}: yes (17.6/4.9)
## : : other_credit = none:
## : : :...existing_loans_count <= 2: no (24.6)
## : : existing_loans_count > 2: yes (2.4/0.3)
## : purpose = furniture/appliances:
## : :...age > 44: no (22.7)
## : age <= 44:
## : :...job = unemployed: no (0)
## : job = unskilled:
## : :...existing_loans_count <= 1: yes (20.9/5.6)
## : : existing_loans_count > 1: no (4.5)
## : job in {management,skilled}:
## : :...dependents > 1: no (6.6)
## : dependents <= 1:
## : :...existing_loans_count <= 1:
## : :...savings_balance in {> 1000 DM,100 - 500 DM,
## : : : 500 - 1000 DM,
## : : : unknown}: no (16.9)
## : : savings_balance = < 100 DM:
## : : :...age <= 22: yes (8.5/1.3)
## : : age > 22: no (43.1/8.8)
## : existing_loans_count > 1:
## : :...housing in {other,rent}: yes (9.9/2.1)
## : housing = own:
## : :...credit_history in {critical,poor,
## : : very good}: no (18.6/1.6)
## : credit_history in {good,perfect}: yes (14.9/4.3)
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...credit_history = perfect: yes (28.1/9.6)
## credit_history = very good:
## :...age <= 23: no (5.5)
## : age > 23: yes (30/8.1)
## credit_history = poor:
## :...percent_of_income <= 1: no (6.5)
## : percent_of_income > 1:
## : :...savings_balance in {500 - 1000 DM,unknown}: no (6.4)
## : savings_balance in {< 100 DM,> 1000 DM,100 - 500 DM}:
## : :...dependents <= 1: yes (25.1/8)
## : dependents > 1: no (5/0.9)
## credit_history = critical:
## :...savings_balance = unknown: no (8.4)
## : savings_balance in {< 100 DM,> 1000 DM,100 - 500 DM,500 - 1000 DM}:
## : :...other_credit = bank: yes (16.2/4.3)
## : other_credit = store: no (3.7/0.9)
## : other_credit = none:
## : :...savings_balance in {> 1000 DM,500 - 1000 DM}: yes (7.3/2.3)
## : savings_balance = 100 - 500 DM: no (5.9)
## : savings_balance = < 100 DM:
## : :...purpose = business: no (4.5/2.2)
## : purpose in {car0,education,renovations}: yes (8.5/2.2)
## : purpose = car:
## : :...age <= 29: yes (6.9)
## : : age > 29: no (25.6/6.9)
## : purpose = furniture/appliances:
## : :...months_loan_duration <= 36: no (38.4/10.9)
## : months_loan_duration > 36: yes (3.8)
## credit_history = good:
## :...amount > 8086: yes (24/3.8)
## amount <= 8086:
## :...phone = yes:
## :...age <= 28: yes (23.9/7.5)
## : age > 28: no (69.4/17.9)
## phone = no:
## :...other_credit in {bank,store}: yes (25.1/7.2)
## other_credit = none:
## :...percent_of_income <= 2:
## :...job in {management,unemployed,unskilled}: no (15.6/2.7)
## : job = skilled:
## : :...amount <= 1386: yes (9.9/1)
## : amount > 1386:
## : :...age <= 24: yes (13.4/4.6)
## : age > 24: no (27.8/3.1)
## percent_of_income > 2:
## :...checking_balance = < 0 DM: yes (62.5/21.4)
## checking_balance = 1 - 200 DM:
## :...months_loan_duration > 42: yes (4.9)
## months_loan_duration <= 42:
## :...existing_loans_count > 1: no (5)
## existing_loans_count <= 1:
## :...age <= 35: no (39.4/13.2)
## age > 35: yes (14.7/4.2)
##
## ----- Trial 7: -----
##
## Decision tree:
##
## checking_balance = unknown:
## :...employment_duration in {> 7 years,4 - 7 years}: no (101.1/20.4)
## : employment_duration = unemployed: yes (16.6/8)
## : employment_duration = < 1 year:
## : :...amount <= 4594: no (30/5.7)
## : : amount > 4594: yes (10.6/0.3)
## : employment_duration = 1 - 4 years:
## : :...dependents > 1: no (8)
## : dependents <= 1:
## : :...months_loan_duration <= 16: no (32.8/5.3)
## : months_loan_duration > 16:
## : :...existing_loans_count > 2: yes (2.7)
## : existing_loans_count <= 2:
## : :...percent_of_income <= 3: no (20.9/5.9)
## : percent_of_income > 3:
## : :...purpose in {business,car0,education}: yes (10.8)
## : purpose in {car,furniture/appliances,
## : renovations}: no (19.7/7.5)
## checking_balance in {< 0 DM,> 200 DM,1 - 200 DM}:
## :...purpose in {car0,education,renovations}: no (67.2/29.2)
## purpose = business:
## :...age > 46: yes (5.2)
## : age <= 46:
## : :...months_loan_duration <= 18: no (17.5)
## : months_loan_duration > 18:
## : :...other_credit in {bank,store}: no (10/0.5)
## : other_credit = none:
## : :...employment_duration in {> 7 years,
## : : unemployed}: yes (6.6)
## : employment_duration in {< 1 year,1 - 4 years,4 - 7 years}:
## : :...age <= 25: yes (4)
## : age > 25: no (19.2/5.6)
## purpose = car:
## :...amount <= 1297: yes (52.4/12.9)
## : amount > 1297:
## : :...percent_of_income <= 2:
## : :...phone = no: no (32.7/6.1)
## : : phone = yes:
## : : :...years_at_residence <= 3: no (20/4.9)
## : : years_at_residence > 3: yes (14.7/3.8)
## : percent_of_income > 2:
## : :...percent_of_income <= 3: yes (33.1/11.3)
## : percent_of_income > 3:
## : :...months_loan_duration <= 18: no (18.2/1.6)
## : months_loan_duration > 18:
## : :...existing_loans_count <= 1: no (19.5/7.2)
## : existing_loans_count > 1: yes (13.8/1)
## purpose = furniture/appliances:
## :...savings_balance = > 1000 DM: no (5.2)
## savings_balance = 100 - 500 DM: yes (18.6/6)
## savings_balance in {< 100 DM,500 - 1000 DM,unknown}:
## :...existing_loans_count > 1:
## :...existing_loans_count > 2: no (3.6)
## : existing_loans_count <= 2:
## : :...housing = other: yes (3.3)
## : housing in {own,rent}:
## : :...savings_balance = 500 - 1000 DM: yes (3.5/1)
## : savings_balance = unknown: no (6.9)
## : savings_balance = < 100 DM:
## : :...age > 54: yes (2.1)
## : age <= 54: [S1]
## existing_loans_count <= 1:
## :...credit_history in {critical,perfect}: yes (20.3/7.6)
## credit_history in {poor,very good}: no (20.8/9.5)
## credit_history = good:
## :...months_loan_duration <= 7: no (11.4)
## months_loan_duration > 7:
## :...other_credit = bank: no (14.2/4.6)
## other_credit = store: yes (11.7/3.9)
## other_credit = none:
## :...percent_of_income <= 1: no (20.5/5.2)
## percent_of_income > 1:
## :...amount > 6078: yes (10.9/1.1)
## amount <= 6078:
## :...dependents > 1: yes (8.7/2.5)
## dependents <= 1: [S2]
##
## SubTree [S1]
##
## employment_duration in {< 1 year,4 - 7 years}: yes (15/2.5)
## employment_duration in {> 7 years,1 - 4 years,unemployed}: no (25.7/2.9)
##
## SubTree [S2]
##
## employment_duration = > 7 years: no (17.9/2.5)
## employment_duration in {< 1 year,1 - 4 years,4 - 7 years,unemployed}:
## :...job = management: no (6.6)
## job = unemployed: yes (1.1)
## job in {skilled,unskilled}:
## :...years_at_residence <= 1: no (11.8/1.8)
## years_at_residence > 1:
## :...checking_balance = > 200 DM: no (14.7/6.3)
## checking_balance = 1 - 200 DM: yes (25.1/8.8)
## checking_balance = < 0 DM:
## :...months_loan_duration <= 16: no (13.8/3.4)
## months_loan_duration > 16: yes (19.1/5.5)
##
## ----- Trial 8: -----
##
## Decision tree:
##
## checking_balance in {< 0 DM,1 - 200 DM}:
## :...credit_history = perfect:
## : :...housing in {other,rent}: yes (8.3)
## : : housing = own:
## : : :...age <= 34: no (16.6/4.7)
## : : age > 34: yes (5.8)
## : credit_history = poor:
## : :...checking_balance = < 0 DM: yes (12/2.7)
## : : checking_balance = 1 - 200 DM:
## : : :...housing = rent: no (8.6)
## : : housing in {other,own}:
## : : :...amount <= 2279: yes (6.8/0.6)
## : : amount > 2279: no (20/5.7)
## : credit_history = very good:
## : :...existing_loans_count > 1: yes (2.5)
## : : existing_loans_count <= 1:
## : : :...age <= 23: no (3.7)
## : : age > 23:
## : : :...amount <= 8386: yes (32.9/8.1)
## : : amount > 8386: no (2.5)
## : credit_history = critical:
## : :...years_at_residence <= 1: no (8)
## : : years_at_residence > 1:
## : : :...savings_balance in {> 1000 DM,100 - 500 DM,500 - 1000 DM,
## : : : unknown}: no (25.5/5.7)
## : : savings_balance = < 100 DM:
## : : :...age > 61: no (6)
## : : age <= 61:
## : : :...existing_loans_count > 2: no (10.7/2.4)
## : : existing_loans_count <= 2:
## : : :...age > 56: yes (5.4)
## : : age <= 56:
## : : :...amount > 2483: yes (34.1/8.9)
## : : amount <= 2483:
## : : :...purpose in {business,education}: yes (4.4)
## : : purpose in {car,car0,furniture/appliances,
## : : renovations}: no (41.4/10.8)
## : credit_history = good:
## : :...amount > 8086: yes (26.6/4.8)
## : amount <= 8086:
## : :...savings_balance in {> 1000 DM,500 - 1000 DM}: no (17.5/5.1)
## : savings_balance = 100 - 500 DM:
## : :...months_loan_duration <= 27: no (21.3/7.1)
## : : months_loan_duration > 27: yes (5.1)
## : savings_balance = unknown:
## : :...age <= 56: yes (44.7/16.9)
## : : age > 56: no (4.4)
## : savings_balance = < 100 DM:
## : :...job = unemployed: yes (0.9)
## : job = management:
## : :...employment_duration in {< 1 year,1 - 4 years,4 - 7 years,
## : : : unemployed}: no (17.3/1.6)
## : : employment_duration = > 7 years: yes (8/1.2)
## : job = unskilled:
## : :...months_loan_duration <= 26: no (59/19.7)
## : : months_loan_duration > 26: yes (3.3)
## : job = skilled:
## : :...purpose in {business,car0,education,
## : : renovations}: yes (16.6/4.1)
## : purpose = car:
## : :...dependents <= 1: yes (27.7/10.6)
## : : dependents > 1: no (8.1/1.4)
## : purpose = furniture/appliances:
## : :...years_at_residence <= 1: no (18.7/6.5)
## : years_at_residence > 1:
## : :...other_credit = bank: yes (4.5)
## : other_credit = store: no (2.3)
## : other_credit = none:
## : :...percent_of_income <= 3: yes (33.5/15)
## : percent_of_income > 3: no (27.3/9.3)
## checking_balance in {> 200 DM,unknown}:
## :...years_at_residence > 2: no (135.6/32.2)
## years_at_residence <= 2:
## :...months_loan_duration <= 8: no (12.9)
## months_loan_duration > 8:
## :...months_loan_duration <= 9: yes (10.4/1.3)
## months_loan_duration > 9:
## :...months_loan_duration <= 16: no (31.3/4.2)
## months_loan_duration > 16:
## :...purpose in {business,car0,renovations}: no (21.3/8.4)
## purpose = education: yes (6.3/0.8)
## purpose = car:
## :...credit_history in {critical,very good}: yes (17.3/2.6)
## : credit_history in {good,perfect,poor}: no (9.6)
## purpose = furniture/appliances:
## :...credit_history in {critical,perfect,
## : very good}: no (5.6)
## credit_history = poor: yes (4.9)
## credit_history = good:
## :...housing in {other,rent}: no (2.6)
## housing = own:
## :...age <= 25: no (6.8)
## age > 25: yes (29.2/10.2)
##
## ----- Trial 9: -----
##
## Decision tree:
##
## checking_balance = unknown:
## :...dependents > 1: no (26)
## : dependents <= 1:
## : :...amount <= 1474: no (39.7)
## : amount > 1474:
## : :...employment_duration in {> 7 years,4 - 7 years}:
## : :...years_at_residence > 2: no (21.8)
## : : years_at_residence <= 2:
## : : :...age <= 23: yes (4.1)
## : : age > 23: no (19.7/4.2)
## : employment_duration in {< 1 year,1 - 4 years,unemployed}:
## : :...purpose in {business,renovations}: yes (23.2/3.6)
## : purpose in {car,car0,education,furniture/appliances}:
## : :...other_credit in {bank,store}: yes (29.1/10.5)
## : other_credit = none:
## : :...purpose in {car,car0}: no (12.3)
## : purpose in {education,furniture/appliances}:
## : :...amount <= 4455: no (23.7/4.4)
## : amount > 4455: yes (11.1/1.3)
## checking_balance in {< 0 DM,> 200 DM,1 - 200 DM}:
## :...percent_of_income <= 2:
## :...amount > 11054: yes (15.7/3.6)
## : amount <= 11054:
## : :...savings_balance in {> 1000 DM,500 - 1000 DM,
## : : unknown}: no (41.5/11.2)
## : savings_balance = 100 - 500 DM:
## : :...other_credit = bank: no (5.1)
## : : other_credit in {none,store}: yes (21.7/9.4)
## : savings_balance = < 100 DM:
## : :...employment_duration in {> 7 years,unemployed}: no (34.6/11.5)
## : employment_duration = 1 - 4 years:
## : :...job = management: yes (5.1/0.8)
## : : job in {skilled,unemployed,unskilled}: no (65.4/15.8)
## : employment_duration = < 1 year:
## : :...amount <= 2327:
## : : :...age <= 34: yes (20.5/1.9)
## : : : age > 34: no (3)
## : : amount > 2327:
## : : :...other_credit = bank: yes (2.8)
## : : other_credit in {none,store}: no (20.1/3.9)
## : employment_duration = 4 - 7 years:
## : :...dependents > 1: no (4.6)
## : dependents <= 1:
## : :...amount <= 6527: no (16.8/7.2)
## : amount > 6527: yes (7)
## percent_of_income > 2:
## :...housing = rent:
## :...checking_balance in {< 0 DM,1 - 200 DM}: yes (69/22.1)
## : checking_balance = > 200 DM: no (3.4)
## housing = other:
## :...existing_loans_count > 1: yes (18.7/5.3)
## : existing_loans_count <= 1:
## : :...savings_balance in {< 100 DM,> 1000 DM,
## : : 500 - 1000 DM}: yes (29.1/8.6)
## : savings_balance in {100 - 500 DM,unknown}: no (15.3/3.2)
## housing = own:
## :...credit_history in {perfect,poor}: yes (26.9/7.4)
## credit_history = very good: no (14.9/5.6)
## credit_history = critical:
## :...other_credit = bank: yes (11.7/3.4)
## : other_credit in {none,store}: no (63/20.3)
## credit_history = good:
## :...other_credit = store: yes (8.9/1.4)
## other_credit in {bank,none}:
## :...age > 54: no (9.5)
## age <= 54:
## :...existing_loans_count > 1: no (10.2/2.7)
## existing_loans_count <= 1:
## :...purpose in {business,renovations}: no (10.1/3.6)
## purpose in {car0,education}: yes (4.7)
## purpose = car:
## :...other_credit = bank: yes (4.9)
## : other_credit = none:
## : :...years_at_residence > 2: no (14.8/4.5)
## : years_at_residence <= 2:
## : :...amount <= 2150: no (14.9/6.2)
## : amount > 2150: yes (11.1)
## purpose = furniture/appliances:
## :...savings_balance = 100 - 500 DM: yes (3.8)
## savings_balance in {> 1000 DM,
## : 500 - 1000 DM}: no (2.8)
## savings_balance in {< 100 DM,unknown}:
## :...months_loan_duration > 39: yes (3.3)
## months_loan_duration <= 39:
## :...dependents <= 1: no (57.6/19.4)
## dependents > 1: yes (4.6/1.1)
##
##
## Evaluation on training data (900 cases):
##
## Trial Decision Tree
## ----- ----------------
## Size Errors
##
## 0 56 133(14.8%)
## 1 34 211(23.4%)
## 2 39 201(22.3%)
## 3 47 179(19.9%)
## 4 46 174(19.3%)
## 5 50 197(21.9%)
## 6 55 187(20.8%)
## 7 50 190(21.1%)
## 8 51 192(21.3%)
## 9 47 169(18.8%)
## boost 34( 3.8%) <<
##
##
## (a) (b) <-classified as
## ---- ----
## 629 4 (a): class no
## 30 237 (b): class yes
##
##
## Attribute usage:
##
## 100.00% checking_balance
## 100.00% purpose
## 97.11% years_at_residence
## 96.67% employment_duration
## 94.78% credit_history
## 94.67% other_credit
## 92.56% job
## 92.11% percent_of_income
## 90.33% amount
## 85.11% months_loan_duration
## 82.78% age
## 82.78% existing_loans_count
## 75.78% dependents
## 71.56% housing
## 70.78% savings_balance
## 49.22% phone
##
##
## Time: 0.1 secscredit_boost_pred10 <- predict(credit_boost10, credit_test)
CrossTable(credit_test$default, credit_boost_pred10,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 100
##
##
## | predicted default
## actual default | no | yes | Row Total |
## ---------------|-----------|-----------|-----------|
## no | 62 | 5 | 67 |
## | 0.620 | 0.050 | |
## ---------------|-----------|-----------|-----------|
## yes | 13 | 20 | 33 |
## | 0.130 | 0.200 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 75 | 25 | 100 |
## ---------------|-----------|-----------|-----------|
##
## ## Making some mistakes more costly than others
# create dimensions for a cost matrix
matrix_dimensions <- list(c("no", "yes"), c("no", "yes"))
names(matrix_dimensions) <- c("predicted", "actual")
matrix_dimensions## $predicted
## [1] "no" "yes"
##
## $actual
## [1] "no" "yes"# build the matrix
error_cost <- matrix(c(0, 1, 4, 0), nrow = 2, dimnames = matrix_dimensions)
error_cost## actual
## predicted no yes
## no 0 4
## yes 1 0# apply the cost matrix to the tree
credit_cost <- C5.0(credit_train[-17], credit_train$default,
costs = error_cost)
credit_cost_pred <- predict(credit_cost, credit_test)
CrossTable(credit_test$default, credit_cost_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 100
##
##
## | predicted default
## actual default | no | yes | Row Total |
## ---------------|-----------|-----------|-----------|
## no | 37 | 30 | 67 |
## | 0.370 | 0.300 | |
## ---------------|-----------|-----------|-----------|
## yes | 7 | 26 | 33 |
## | 0.070 | 0.260 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 44 | 56 | 100 |
## ---------------|-----------|-----------|-----------|
##
## #### Part 2: Rule Learners -------------------
## Example: Identifying Poisonous Mushrooms ----
## Step 2: Exploring and preparing the data ----
mushrooms <- read.csv("mushrooms.csv", stringsAsFactors = TRUE)
# examine the structure of the data frame
str(mushrooms)## 'data.frame': 8124 obs. of 23 variables:
## $ type : Factor w/ 2 levels "edible","poisonous": 2 1 1 2 1 1 1 1 2 1 ...
## $ cap_shape : Factor w/ 6 levels "bell","conical",..: 3 3 1 3 3 3 1 1 3 1 ...
## $ cap_surface : Factor w/ 4 levels "fibrous","grooves",..: 4 4 4 3 4 3 4 3 3 4 ...
## $ cap_color : Factor w/ 10 levels "brown","buff",..: 1 10 9 9 4 10 9 9 9 10 ...
## $ bruises : Factor w/ 2 levels "no","yes": 2 2 2 2 1 2 2 2 2 2 ...
## $ odor : Factor w/ 9 levels "almond","anise",..: 8 1 2 8 7 1 1 2 8 1 ...
## $ gill_attachment : Factor w/ 2 levels "attached","free": 2 2 2 2 2 2 2 2 2 2 ...
## $ gill_spacing : Factor w/ 2 levels "close","crowded": 1 1 1 1 2 1 1 1 1 1 ...
## $ gill_size : Factor w/ 2 levels "broad","narrow": 2 1 1 2 1 1 1 1 2 1 ...
## $ gill_color : Factor w/ 12 levels "black","brown",..: 1 1 2 2 1 2 5 2 8 5 ...
## $ stalk_shape : Factor w/ 2 levels "enlarging","tapering": 1 1 1 1 2 1 1 1 1 1 ...
## $ stalk_root : Factor w/ 5 levels "bulbous","club",..: 3 2 2 3 3 2 2 2 3 2 ...
## $ stalk_surface_above_ring: Factor w/ 4 levels "fibrous","scaly",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ stalk_surface_below_ring: Factor w/ 4 levels "fibrous","scaly",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ stalk_color_above_ring : Factor w/ 9 levels "brown","buff",..: 8 8 8 8 8 8 8 8 8 8 ...
## $ stalk_color_below_ring : Factor w/ 9 levels "brown","buff",..: 8 8 8 8 8 8 8 8 8 8 ...
## $ veil_type : Factor w/ 1 level "partial": 1 1 1 1 1 1 1 1 1 1 ...
## $ veil_color : Factor w/ 4 levels "brown","orange",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ ring_number : Factor w/ 3 levels "none","one","two": 2 2 2 2 2 2 2 2 2 2 ...
## $ ring_type : Factor w/ 5 levels "evanescent","flaring",..: 5 5 5 5 1 5 5 5 5 5 ...
## $ spore_print_color : Factor w/ 9 levels "black","brown",..: 1 2 2 1 2 1 1 2 1 1 ...
## $ population : Factor w/ 6 levels "abundant","clustered",..: 4 3 3 4 1 3 3 4 5 4 ...
## $ habitat : Factor w/ 7 levels "grasses","leaves",..: 5 1 3 5 1 1 3 3 1 3 ...# drop the veil_type feature
mushrooms$veil_type <- NULL
# examine the class distribution
table(mushrooms$type)##
## edible poisonous
## 4208 3916set.seed(123)
train_sample <- sample(8124, 7000)
str(train_sample)## int [1:7000] 2337 6404 3322 7171 7637 370 4288 7244 4476 3706 ...# split the data frames
mushrooms_train <- mushrooms[train_sample, ]
mushrooms_test <- mushrooms[-train_sample, ]
## Step 3: Training a model on the data ----
library(RWeka)## Warning: package 'RWeka' was built under R version 3.3.3# train OneR() on the data
mushroom_1R <- OneR(type ~ ., data = mushrooms_train)
## Step 4: Evaluating model performance ----
mushroom_1R## odor:
## almond -> edible
## anise -> edible
## creosote -> poisonous
## fishy -> poisonous
## foul -> poisonous
## musty -> poisonous
## none -> edible
## pungent -> poisonous
## spicy -> poisonous
## (6895/7000 instances correct)summary(mushroom_1R)##
## === Summary ===
##
## Correctly Classified Instances 6895 98.5 %
## Incorrectly Classified Instances 105 1.5 %
## Kappa statistic 0.9699
## Mean absolute error 0.015
## Root mean squared error 0.1225
## Relative absolute error 3.0039 %
## Root relative squared error 24.5108 %
## Total Number of Instances 7000
##
## === Confusion Matrix ===
##
## a b <-- classified as
## 3626 0 | a = edible
## 105 3269 | b = poisonousmushroom_pred <- predict(mushroom_1R, mushrooms_test)
# cross tabulation of predicted versus actual classes
library(gmodels)
CrossTable(mushrooms_test$type, mushroom_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 1124
##
##
## | predicted default
## actual default | edible | poisonous | Row Total |
## ---------------|-----------|-----------|-----------|
## edible | 582 | 0 | 582 |
## | 0.518 | 0.000 | |
## ---------------|-----------|-----------|-----------|
## poisonous | 15 | 527 | 542 |
## | 0.013 | 0.469 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 597 | 527 | 1124 |
## ---------------|-----------|-----------|-----------|
##
## ## Step 5: Improving model performance ----
mushroom_JRip <- JRip(type ~ ., data = mushrooms_train)
mushroom_JRip## JRIP rules:
## ===========
##
## (odor = foul) => type=poisonous (1860.0/0.0)
## (gill_size = narrow) and (gill_color = buff) => type=poisonous (986.0/0.0)
## (gill_size = narrow) and (odor = pungent) => type=poisonous (222.0/0.0)
## (odor = creosote) => type=poisonous (171.0/0.0)
## (spore_print_color = green) => type=poisonous (65.0/0.0)
## (stalk_surface_below_ring = scaly) and (stalk_surface_above_ring = silky) => type=poisonous (58.0/0.0)
## (habitat = leaves) and (cap_surface = scaly) and (population = clustered) => type=poisonous (10.0/0.0)
## (cap_surface = grooves) => type=poisonous (2.0/0.0)
## => type=edible (3626.0/0.0)
##
## Number of Rules : 9summary(mushroom_JRip)##
## === Summary ===
##
## Correctly Classified Instances 7000 100 %
## Incorrectly Classified Instances 0 0 %
## Kappa statistic 1
## Mean absolute error 0
## Root mean squared error 0
## Relative absolute error 0 %
## Root relative squared error 0 %
## Total Number of Instances 7000
##
## === Confusion Matrix ===
##
## a b <-- classified as
## 3626 0 | a = edible
## 0 3374 | b = poisonousmushroom_pred <- predict(mushroom_JRip, mushrooms_test)
# cross tabulation of predicted versus actual classes
library(gmodels)
CrossTable(mushrooms_test$type, mushroom_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 1124
##
##
## | predicted default
## actual default | edible | poisonous | Row Total |
## ---------------|-----------|-----------|-----------|
## edible | 582 | 0 | 582 |
## | 0.518 | 0.000 | |
## ---------------|-----------|-----------|-----------|
## poisonous | 0 | 542 | 542 |
## | 0.000 | 0.482 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 582 | 542 | 1124 |
## ---------------|-----------|-----------|-----------|
##
## # Rule Learner Using C5.0 Decision Trees (not in text)
library(C50)
mushroom_c5rules <- C5.0(type ~ odor + gill_size, data = mushrooms_train, rules = TRUE)
mushroom_c5rules##
## Call:
## C5.0.formula(formula = type ~ odor + gill_size, data =
## mushrooms_train, rules = TRUE)
##
## Rule-Based Model
## Number of samples: 7000
## Number of predictors: 2
##
## Number of Rules: 2
##
## Non-standard options: attempt to group attributessummary(mushroom_c5rules)##
## Call:
## C5.0.formula(formula = type ~ odor + gill_size, data =
## mushrooms_train, rules = TRUE)
##
##
## C5.0 [Release 2.07 GPL Edition] Sun Apr 30 19:56:18 2017
## -------------------------------
##
## Class specified by attribute `outcome'
##
## Read 7000 cases (3 attributes) from undefined.data
##
## Rules:
##
## Rule 1: (3731/105, lift 1.9)
## odor in {almond, anise, none}
## -> class edible [0.972]
##
## Rule 2: (3269, lift 2.1)
## odor in {creosote, fishy, foul, musty, pungent, spicy}
## -> class poisonous [1.000]
##
## Default class: edible
##
##
## Evaluation on training data (7000 cases):
##
## Rules
## ----------------
## No Errors
##
## 2 105( 1.5%) <<
##
##
## (a) (b) <-classified as
## ---- ----
## 3626 (a): class edible
## 105 3269 (b): class poisonous
##
##
## Attribute usage:
##
## 100.00% odor
##
##
## Time: 0.0 secsmushroom_pred <- predict(mushroom_c5rules, mushrooms_test)
# cross tabulation of predicted versus actual classes
library(gmodels)
CrossTable(mushrooms_test$type, mushroom_pred,
prop.chisq = FALSE, prop.c = FALSE, prop.r = FALSE,
dnn = c('actual default', 'predicted default'))##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 1124
##
##
## | predicted default
## actual default | edible | poisonous | Row Total |
## ---------------|-----------|-----------|-----------|
## edible | 582 | 0 | 582 |
## | 0.518 | 0.000 | |
## ---------------|-----------|-----------|-----------|
## poisonous | 15 | 527 | 542 |
## | 0.013 | 0.469 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 597 | 527 | 1124 |
## ---------------|-----------|-----------|-----------|
##
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