python - How can I analyze a confusion matrix? -

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when print out scikit-learn's confusion matrix, receive huge matrix. want analyze true positives, true negatives etc. how can so? how confusion matrix looks like. wish understand better.

[[4015  336    0 ...,    0    0    2]  [ 228 2704    0 ...,    0    0    0]  [   4    7   19 ...,    0    0    0]  ...,   [   3    2    0 ...,    5    0    0]  [   1    1    0 ...,    0    0    0]  [  13    1    0 ...,    0    0   11]]

iiuc, question undefined. "false positives", "true negatives" - these terms defined binary classification. read more definition of confusion matrix.

in case, confusion matrix of dimension n x n. each diagonal represents, entry (i, i) case prediction i , outcome i too. other off-diagonal entry indicates mistake prediction i , outcome j. there no meaning "positive" , "negative in case.

you can find diagnoal elements using np.diagonal, and, following that, easy sum them. sum of wrong cases sum of matrix minus sum of diagonal.


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