13. Models That Engineer Features for Us
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# setup from mlwpy import * %matplotlib inline* kwargs = {'test_size':.25, 'random_state':42} iris = datasets.load_iris() tts = skms.train_test_split(iris.data, iris.target, **kwargs) (iris_train, iris_test, iris_train_tgt, iris_test_tgt) = tts wine = datasets.load_wine() tts = skms.train_test_split(wine.data, wine.target, **kwargs) (wine_train, wine_test, wine_train_tgt, wine_test_tgt) = tts diabetes = datasets.load_diabetes() tts = skms.train_test_split(diabetes.data, diabetes.target, **kwargs) (diabetes_train_ftrs, diabetes_test_ftrs, diabetes_train_tgt, diabetes_test_tgt) = tts # these are entire datasets iris_df = pd.DataFrame(iris.data, columns=iris.feature_names) ...
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