我有一个分类报告,例如:
from sklearn.metrics import classification_report
print(classification_report(y_test, y_pred))
输出:
precision recall f1-score support
0.0 1.00 1.00 1.00 15
1.0 1.00 0.95 0.98 22
2.0 0.93 1.00 0.96 13
accuracy 0.98 50
macro avg 0.98 0.98 0.98 50
weighted avg 0.98 0.98 0.98 50
如何获得精度并从中恢复?
答案 0 :(得分:2)
您可以使用 precision_recall_fscore_support()函数。
const request = require('request');
const endpoint = 'http://localhost:3000/city';
//get
it('should return 200 response code', function (done) {
request.get(endpoint, function (error, response) {
expect(response.statusCode).toEqual(200);
done();
});
});
//post
it('should fail on POST', function (done) {
request.post(endpoint, {json: true, body: {}}, function (error, response) {
expect(response.statusCode).toEqual(404);
done();
});
});
有关更多详细信息,请参阅文档1 precision_recall_fscore_support: