classification report scikit
from sklearn.metrics import classification_report
target_names = ['first_value_y','second_value_y'] # target values
# Print classification report after a train/test split:
print(classification_report(y_test, y_pred, target_names=target_names))classification report to excel
import pandas as pd
def classification_report_csv(report):
report_data = []
lines = report.split('\n')
for line in lines[2:-3]:
row = {}
row_data = line.split(' ')
row['class'] = row_data[0]
row['precision'] = float(row_data[1])
row['recall'] = float(row_data[2])
row['f1_score'] = float(row_data[3])
row['support'] = float(row_data[4])
report_data.append(row)
dataframe = pd.DataFrame.from_dict(report_data)
dataframe.to_csv('classification_report.csv', index = False)
report = classification_report(y_true, y_pred)
classification_report_csv(report)Copyright © 2021 Codeinu
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