39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
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# 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 a sample dataset for clustering evaluations
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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", "three_blobs.csv.gz")
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def three_blobs_data():
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"""A random dataset of 3 2D blobs for clustering.
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Number of samples : 150
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Suggested labels : {0, 1, 2}, distribution: [50, 50, 50]
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Returns
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--------
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X, y : [n_samples, n_features], [n_cluster_labels]
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X is the feature matrix with 159 samples as rows
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and 2 feature columns.
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y is a 1-dimensional array of the 3 suggested cluster 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/three_blobs_data
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"""
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tmp = np.genfromtxt(fname=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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