April 2020
Intermediate to advanced
344 pages
8h 22m
Japanese
Content preview from Pythonではじめる教師なし学習 ―機械学習の可能性を広げるラベルなしデータの利用
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章 機械学習プロジェクトのはじめから終わりまで
gbm.predict(X_train_fold, num_iteration=gbm.best_iteration))
trainingScores.append(loglossTraining)
predictionsBasedOnKFoldsEnsemble.loc[X_cv_fold.index,'prediction'] = \
gbm.predict(X_cv_fold, num_iteration=gbm.best_iteration)
loglossCV = log_loss(y_cv_fold, \
predictionsBasedOnKFoldsEnsemble.loc[X_cv_fold.index,'prediction'])
cvScores.append(loglossCV)
print('Training Log Loss: ', loglossTraining)
print('CV Log Loss: ', loglossCV)
loglossEnsemble = log_loss(y_train, \
predictionsBasedOnKFoldsEnsemble.loc[:,'prediction'])
print('Ensemble Log Loss: ', loglossEnsemble)
Ensemble Log Loss: 0.002885415974220497
2.9.1.4
結果の評価 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.