56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
# Sebastian Raschka 2014-2020
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# mlxtend Machine Learning Library Extensions
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#
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# A function for loading the open-source Wine dataset.
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# Author: Sebastian Raschka <sebastianraschka.com>
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#
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# License: BSD 3 clause
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import numpy as np
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import os
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this_dir, this_filename = os.path.split(__file__)
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DATA_PATH = os.path.join(this_dir, "data", "wine.csv")
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def wine_data():
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"""Wine dataset.
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Source : https://archive.ics.uci.edu/ml/datasets/Wine
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Number of samples : 178
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Class labels : {0, 1, 2}, distribution: [59, 71, 48]
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Dataset Attributes:
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- 1) Alcohol
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- 2) Malic acid
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- 3) Ash
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- 4) Alcalinity of ash
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- 5) Magnesium
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- 6) Total phenols
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- 7) Flavanoids
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- 8) Nonflavanoid phenols
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- 9) Proanthocyanins
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- 10) Color intensity
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- 11) Hue
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- 12) OD280/OD315 of diluted wines
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- 13) Proline
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Returns
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--------
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X, y : [n_samples, n_features], [n_class_labels]
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X is the feature matrix with 178 wine samples as rows
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and 13 feature columns.
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y is a 1-dimensional array of the 3 class labels 0, 1, 2
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Examples
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-----------
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For usage examples, please see
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http://rasbt.github.io/mlxtend/user_guide/data/wine_data
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"""
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tmp = np.loadtxt(DATA_PATH, delimiter=',')
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X, y = tmp[:, :-1], tmp[:, -1]
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y = y.astype(int)
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return X, y
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