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sklbench/datasets/common.py

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@@ -23,8 +23,12 @@
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import pandas as pd
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from scipy.sparse import csr_matrix
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from sklearn.model_selection import train_test_split
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from sklearn.preprocessing import OneHotEncoder, OrdinalEncoder
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from sklearn.preprocessing import MinMaxScaler, StandardScaler
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from sklearn.preprocessing import (
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MinMaxScaler,
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OneHotEncoder,
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OrdinalEncoder,
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StandardScaler,
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)
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from ..utils.custom_types import Array
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from ..utils.logger import logger

sklbench/datasets/loaders.py

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}
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return {"x": x, "y": y}, data_desc
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@preprocess
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@cache
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def load_gisette(
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data_desc = {"n_classes": 2, "default_split": {"test_size": 0.2, "random_state": 42}}
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return {"x": x, "y": y}, data_desc
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@preprocess
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@cache
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def load_cifar(

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