https://ask.ghassem.com/tag/sklearn Powered by Question2Answer https://ask.ghassem.com/819/can-use-single-pipeline-for-multiple-estimators-scikit-learn Is there any proper way to combine multiple classifiers and their parameter grids in one Pipeline? Machine Learning https://ask.ghassem.com/819/can-use-single-pipeline-for-multiple-estimators-scikit-learn Tue, 18 Feb 2020 14:14:30 +0000 https://ask.ghassem.com/777/score-vs-accuracyscore-in-sklearn Hi,<br /> <br /> Since I still have confuse to use the score() &nbsp;and accuracy_score(), so I want to confirm my test assumption.<br /> Q1: score(), we use the split data to test the accuracy by knn.score(X_test, y_test) to prevent bias using the same training data, right? here knn.score(X_test, y_test) just compare the pair of test value.<br /> <br /> Q2: accuracy_score from sklearn.metrics to test the predicted output of target value &quot;y_pred&quot; with the y_test, using accuracy_score(y_test, y_pred), just compare the actual target value and predicted target value?<br /> <br /> Q3.My result is the same after using both methods, are they doing the same thing?<br /> <br /> Q4.using accuracy_score(), I can using to compare the split training target data y_train with the y_train_pred(return form knn.predict(X_train) ). Then it should be OK now, using it to show the accuracy by accuracy_score(y_train, y_train_pred), since the prediction is done and just compare the original data, then the bias does not exist?<br /> <br /> Thanks. Machine Learning https://ask.ghassem.com/777/score-vs-accuracyscore-in-sklearn Tue, 21 Jan 2020 21:28:11 +0000