Confusion Matrix of LSTM using Sklear getting error I want to calculate the confusion Matrix of my LSTM model. Shape of y_test= (17799,1) y_Pred= (17799,1) I used thefollowing code:from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, y_pred)getting following error: raise ValueError("{0} is not supported".format(y_type))

ValueError: continuous is not supported
both y_test and y_predict are normalized using minmaxscaler(0,1)
first few rows of both varaibles looks like:
y_test={0,0,0,0.0216212}
y_predict={0.000433061,0.000433061,0.000433061,0.000450924}

Please suggest how to calculated confusion matrix, tp,fp,tn,fn .
A confusion matrix can be drawn for a classification problem, where the Machine Learning Model (in your case LSTM) predicts the target variable into one of the N classes.

Can you confirm that your problem is a Classification problem and not a Regression one?

If in case you have a regression problem, then you might want to use a different evaluation metric.