Beispiel #1
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def train_mlp_model_refined():
    data = ml.ModalData()
    data.log_transform()
    data.min_max_scaler()
    data.factorize()
    data.pca(16)
    data.train_mlp_refined()
Beispiel #2
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def confusion_matrix():
    data = ml.ModalData()
    data.log_transform()
    data.min_max_scaler()
    data.factorize()
    data.pca(16)
    data.confusion_matrix()
Beispiel #3
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def train_random_forest_model():
    data = ml.ModalData()
    data.log_transform()
    data.min_max_scaler()
    data.factorize()
    data.pca(16)
    data.train_random_forest()
Beispiel #4
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def data_exploration():
    data = ml.ModalData()
    data.explore_num_features()
    data.explore_cat_features()
    data.data_explore()
Beispiel #5
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def identify_outliers():
    data = ml.ModalData()
    data.log_transform()
    data.identify_outliers()
Beispiel #6
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def data_preprocessing():
    data = ml.ModalData()
    data.log_transform()
    data.min_max_scaler()
    data.factorize()
    data.pca(41)
Beispiel #7
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def data_visualization():
    data = ml.ModalData()
    data.initial_heatmap()
    data.initial_distplot()