[英]How to find TN,TP,FN,FP from matrix in python?
我有這樣的代碼。
import numpy as np
confusion_matrix = [[6,0,0,0,0],
[0,62,1,1,0],
[0,0,30,0,0],
[0,1,0,41,0],
[0,0,0,0,2]]
confusion_matrix=np.matrix(confusion_matrix)
FP = confusion_matrix.sum(axis=0) - np.diag(confusion_matrix)
FN = confusion_matrix.sum(axis=1) - np.diag(confusion_matrix)
TP = np.diag(confusion_matrix)
TN = confusion_matrix.values.sum() - (FP + FN + TP)
# Sensitivity, hit rate, recall, or true positive rate
TPR = TP/(TP+FN)
# Specificity or true negative rate
TNR = TN/(TN+FP)
# Precision or positive predictive value
PPV = TP/(TP+FP)
# Negative predictive value
NPV = TN/(TN+FN)
# Fall out or false positive rate
FPR = FP/(FP+TN)
# False negative rate
FNR = FN/(TP+FN)
# False discovery rate
FDR = FP/(TP+FP)
# Overall accuracy
ACC = (TP+TN)/(TP+FP+FN+TN)
但它給出了這樣的錯誤。
AttributeError: 'matrix' object has no attribute 'values' 如何找到給定矩陣的所有 TP、FP、TN、FN。
將此confusion_matrix.values.sum() - (FP + FN + TP)
更改為
confusion_matrix.sum() - (FP + FN + TP)
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