python-scikit-learnHow to generate dataset for classification
import numpy as np
from sklearn import datasets
X, y = datasets.make_classification(100, 5, n_classes=2)ctrl + cfrom sklearn importimport module from scikit-learn | import numpyimport Numpy module |
X, yloaded features data ( | datasetspredefined datasets to play with |
make_classificationgenerates dataset for classification models | 100number of generated objects |
5number of features | n_classesnumber of generated classes |
Usage example
import numpy as np
from sklearn import datasets
X, y = datasets.make_classification(100, 5, n_classes=2)
print(X.shape)
print(y)output
(100, 5)
[1 1 1 1 0 0 1 1 0 0 0 0 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0
0 1 1 1 0 1 1 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 1 0 1 1 1 0 1 1 0 1 1 0 1 1 1
0 1 0 0 0 1 0 1 0 0 0 1 1 1 1 0 1 0 0 0 0 0 1 0 1 1]
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