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This article mainly explains "python how to output classification_report to csv file", the content of the article is simple and clear, easy to learn and understand, the following please follow the editor's ideas slowly in depth, together to study and learn "python how to output classification_report to csv file" bar!

My pandas version:

Pandas 1.0.3

Code: from sklearn.metrics import classification_reportreport = classification_report (y_test, y_pred, output_dict=True) df = pd.DataFrame (report). Transpose () df.to_csv ("result.csv", index= True)

Is it very simple? here is a result that I have derived:

Supplement: sklearn classification_report output description

Svm-rbf0.606

Precision recall f1-score support0.0 0.56 0.39 0.46 4311.0 0.62 0.77 0.69 569avg / total 0.60 0.61 0.59 1000

The last line is calculated using the support weighted average, such as 0.59 = (431-0.46-569-0.69) / 1000

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