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A confusion matrix is a contingency table used to evaluate the predictive accuracy of a classifier. Confusion matrix is the 2x2 frequency table with counts "True positive", "True negative", "False positive", "False negative", relating classifying to a class of interest vs. else class. But in a broader sense, any frequency kxk crosstabulation "Predicted" x "Actual" classes can be called a confusion matrix, in the context of evaluation of a classifier.

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How to understand confusion matrix for 3x3

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 log_reg=Logist …
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