CODEWITHSUNDEEP
rdecision-tree
vijay MV
vijay MV

Reputation: 75

Why am i getting an error while trying to make a confusion matrix in decision tree?

I am learning how to use decision trees in r.

I made a model and did a prediction. I want to check the accuracy of my model. But when ever i tried to make confusion matrix using table function I am getting the error:

Error in table(test_data$Outcome, predictn) : all arguments must have the same length

The code I used is:

data =  read.csv("C:/Users/VIJAY/Desktop/ML/logistic regression/diabetes.csv")

head(data)
dim(data)


library(rpart)
library(rpart.plot)
library(caret)

s = sample(768,600)

train_data = data[s,]
test_data = data[-s,]

model = rpart(Outcome ~.,data = train_data, method = "class")
rpart.plot(model,cex = .9)

predictn = predict(model,data= test_data,type = "class")

tab = table(test_data$Outcome,predictn)

Upvotes: 0

Views: 286

Answers (1)

Gateux
Gateux

Reputation: 63

Your response from the test set and predictions have different lengths. I would say that predictions weren't made for all observations (maybe because of missing values of some predictors - for this consider using surrogate variables or deleting the rows which have missing values in these predictors in the test set).

btw, when you are using caret, there is a nice function caret::confusionMatrix()

Upvotes: 2

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