/knn_score_calculate

accuracy-precision- recall- f1score

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knn_score_calculate

accuracy-precision- recall- f1score Accuracy measures how many classifications your algorithm got correct out of every classification it made. Recall measures the percentage of the relevant items your classifier was able to successfully find. Precision measures the percentage of items your classifier found that were actually relevant. Precision and recall are tied to each other. As one goes up, the other will go down. F1 score is a combination of precision and recall. F1 score will be low if either precision or recall is low

----copied from codecademy.com----