homework for data minine
Python
sklearn
numpy
TP----the number of true sample to predict as true (true positive)
FN----the number of true sample to predict as false (false negative)
FP----the number of false sample to predict as true (false positive)
TN----the number of false sample to predict as false (true negative)
Precision------P=TP/(TP+FP)
recall-----------R=TP/(TP+FN)
F1---------------F1=2TP/(2TP+FP+FN) 2/F1=1/P+1/R
accuracy-------A=(TP+TN)/(TP+FN+FP+TN)
https://en.wikipedia.org/wiki/Precision_and_recall
https://en.wikipedia.org/wiki/Accuracy_and_precision