dataset can be find here : https://archive.ics.uci.edu/ml/datasets/Bank+Marketing#
set.seed(1234)
ind <- sample(2, nrow(bank), replace = TRUE, prob = c(0.7, 0.3))
train.data <- bank[ind == 1, ]
test.data <- bank[ind == 2, ]
I was searching my problem i tried to set it to factor in confusion matrix. But problem didn't solved at all
cartmodel <- rpart(y ~., data = train.data)
cartmodel
cart.pred = predict(cartmodel, test.data)
summary(cart.pred)
confusionMatrix(as.factor(cart.pred),as.factor(test.data$y))
confusionMatrix
What i need to change? Dataset is Bank.. so Num and Factor attributes.
Update : i tried change all atributed to factor.. still error
Using the csv from UCI (can also try this link):
library(rpart)
library(caret)
bank = read.csv("../bank/bank-full.csv",sep=";")
set.seed(1234)
ind <- sample(2, nrow(bank), replace = TRUE, prob = c(0.7, 0.3))
train.data <- bank[ind == 1, ]
test.data <- bank[ind == 2, ]
When you call predict() you are getting the probabilities, not the labels:
cartmodel <- rpart(y ~., data = train.data)
cart.pred = predict(cartmodel, test.data)
head(cart.pred)
no yes
5 0.9393461 0.06065387
14 0.9393461 0.06065387
16 0.9393461 0.06065387
26 0.9393461 0.06065387
28 0.9393461 0.06065387
29 0.9393461 0.06065387
To get labels:
cart.pred = predict(cartmodel, test.data,type="class")
confusionMatrix(cart.pred,test.data$y)
Confusion Matrix and Statistics
Reference
Prediction no yes
no 11710 1039
yes 302 517
Accuracy : 0.9012
95% CI : (0.896, 0.9061)
No Information Rate : 0.8853
P-Value [Acc > NIR] : 1.831e-09
Kappa : 0.3869