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Explain about confusion matrix in r?
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Answer / Suman Pal
"A confusion matrix is a table used to describe the performance of a classification model. It summarizes the number of true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN) for a binary classification problem.nnIn R, you can use the caret package to calculate a confusion matrix:n```Rnlibrary(caret)nn# Train a classification modelnmodel <- train(y ~ ., data = training_data, method = 'naive_bayes')nn# Predict on new datanpredictions <- predict(model, newdata = testing_data)nn# Calculate the confusion matrixnconfusionMatrix(predict(model, newdata = testing_data), testing_data$y)n```
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