I used Sklearn logistic regression for multiclass classifier to classify as Male , Female and Infant on abalone data set Below is my sample Logistic regression for multi classifier
x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.20,random_state=False) log_reg=LogisticRegression() log_model=log_reg.fit(x_train,y_train) pred=log_model.predict(x_test) confusion_matrix(y_test,pred)
Below is my confusion Matrix
M F I --- predicted M [[ 64, 46, 39], F [ 12, 237,42], I [ 52, 79, 165]] actual vs Predicted
Consider a case of 2X2 where I classified patient as HIV positive --1
1 0 --- predicted 1 [[ 1--TP, 0--FN], 0 [ 1--FP, 0--TN ]] Act vs Predicted
unlike 2 x 2 I am unable to extrapolate it to N X N only I can make out is 64 I predicted as Male and which is Actually male as True Positive My question is how can I identify True Negative , False Positive , false Negative .