ML之xgboost:利用xgboost算法(自带方式)训练mushroom蘑菇数据集(22+1,6513+1611)来预测蘑菇是否毒性(二分类预测)
目录
1、xgboost(num_trees=0): Binary prediction based on Mushroom Dataset
2、xgboost(num_trees=1): Binary prediction based on Mushroom Dataset
3、xgboost(num_trees=1,max_depth=4): Binary prediction based on Mushroom Dataset
数据集:Dataset之mushroom:mushroom蘑菇数据集的简介、下载、使用方法之详细攻略
- preds = bst.predict(dtest)
- predictions = [round(value) for value in preds]
- test_accuracy = accuracy_score(y_test, predictions)
- print("Test Accuracy: %.2f%%" % (test_accuracy * 100.0))
-
-
- from matplotlib import pyplot
- import graphviz
-
- num_trees=0
- xgb.plot_tree(bst, num_trees=0, rankdir= 'LR' )
- xgb.to_graphviz(bst,num_trees=0)
-
-
- num_trees=1
- xgb.plot_tree(bst,num_trees=1, rankdir= 'LR' )
- xgb.to_graphviz(bst,num_trees=1)
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