StandadScaler和Pipeline函数用法语法

Question

我想知道＆＃34; estimator＆＃34;变量do以及它如何随着程序的流程而变化。

同样，请解释＆＃34; Pipeline＆＃34;在这里运作。

我很难从Scikit-learn网站上了解它。

# evaluate baseline model with standardized dataset
numpy.random.seed(seed)
estimators = []
estimators.append(('standardize', StandardScaler()))
estimators.append(('mlp', KerasClassifier(build_fn=create_baseline, nb_epoch=100, batch_size=5, verbose=0)))
pipeline = Pipeline(estimators)
kfold = StratifiedKFold(y=encoded_Y, n_folds=10, shuffle=True, random_state=seed)
results = cross_val_score(pipeline, X, encoded_Y, cv=kfold)
print("Standardized: %.2f%% (%.2f%%)" % (results.mean()*100, results.std()*100))