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from sklearn import datasets import numpy as np X, y = datasets.make_blobs(n_features=2, centers=2) from sklearn.svm import LinearSVC from sklearn.svm
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posted @ 2016-03-31 22:47
qqhfeng16
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http://docs.scipy.org/doc/numpy/reference/generated/numpy.percentile.html numpy.percentile(a, q, axis=None, out=None, overwrite_input=False, interpola
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posted @ 2016-03-31 21:56
qqhfeng16
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#调整随机森林的参数(调整n_estimators随机森林中树的数量默认10个树,精度递增显著) from sklearn import datasets X, y = datasets.make_classification(n_samples=10000,n_features=20,n_informative=15,flip_y=.5, weights=[.2, .8]) import ...
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posted @ 2016-03-31 18:36
qqhfeng16
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posted @ 2016-03-31 18:11
qqhfeng16
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