8000 simplifying column transformer example by removing default values by amueller · Pull Request #11958 · scikit-learn/scikit-learn · GitHub
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simplifying column transformer example by removing default values #11958

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Sep 1, 2018
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simplifying column transformer example by removing default values #11958

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8 changes: 3 additions & 5 deletions examples/compose/plot_column_transformer_mixed_types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,13 +61,12 @@
categorical_features = ['embarked', 'sex', 'pclass']
categorical_transformer = Pipeline(steps=[
('imputer', SimpleImputer(strategy='constant', fill_value='missing')),
('onehot', OneHotEncoder(sparse=False, handle_unknown='ignore'))])
('onehot', OneHotEncoder(handle_unknown='ignore'))])

preprocessor = ColumnTransformer(
transformers=[
('num', numeric_transformer, numeric_features),
('cat', categorical_transformer, categorical_features)],
remainder='drop')
('cat', categorical_transformer, categorical_features)])

# Append classifier to preprocessing pipeline.
# Now we have a full prediction pipeline.
Expand All @@ -77,8 +76,7 @@
X = data.drop('survived', axis=1)
y = data['survived']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,
shuffle=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

clf.fit(X_train, y_train)
print("model score: %.3f" % clf.score(X_test, y_test))
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