Python으로 Machine Learning을 활용한 CTR 예측
Kevin Huo
Instructor
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.neural_network import MLPClassifier
classifier.fit(X_train, y_train)으로 학습predict_proba()와 predict()로 예측max_depth, min_samples_splitn_estimators, oob_scorefit_intercept, class_weighthidden_layer_sizes, max_iterconfusion_matrix(y_test, y_pred)precision_score(y_test, y_pred)recall_score(y_test, y_pred)fbeta_score(y_test, y_pred, beta = 0.5)roc_auc_score(y_test, y_score[:, 1])Python으로 Machine Learning을 활용한 CTR 예측