X, y= datasets.make_classification(n_samples=10000,n_features=20,n_informative=15,flip_y=.5, weights=[.2, .8])importnumpy as np training= np.random.choice([True, False], p=[.8, .2],size=y.shape)fromsklearn.ensembleimportRandomForestClassifierfromsklearn.metricsimportconfusion_matrix n...
# 需要导入模块: from sklearn.ensemble import RandomForestClassifier [as 别名]# 或者: from sklearn.ensemble.RandomForestClassifier importverbose[as 别名]defbuild_model(self, move_number):"""given a move_number, generate a model from npboard picked files and pickle model"""X_train, y_train, ...
如何调整随机森林的参数达到更好的效果。 2016-10-07 22:17 −原文地址: https://www.analyticsvidhya.com/blog/2015/06/tuning-random-forest-model/ A month back, I participated in a Kaggle competition cal... 问道大数据 0 15789 #调整随机森林的参数(调整max_features,结果未见明显差异) ...