2、 决策树可视化方法2,需要安装graphviz软件包 importgraphvizdefDecisionTree_plot2(x,y,feature_names=None,target_names=None,max_depth=3,min_samples_leaf=10): clf = DecisionTreeClassifier(max_depth=max_depth,min_samples_leaf=min_samples_leaf).fit(x,y) dot_data = tree.export_graphviz(clf, fe...
from graphviz import Digraph except ImportError: raise ImportError('You must install graphviz to plot tree') if not isinstance(booster, (Booster, XGBModel)): raise ValueError('booster must be Booster or XGBModel instance') if isinstance(booster, XGBModel): booster = booster.get_booster() tree ...
# 需要导入模块: import xgboost [as 别名]# 或者: from xgboost importXGBModel[as 别名]defto_graphviz(self, num_trees=0, rankdir='UT', yes_color='#0000FF', no_color='#FF0000', **kwargs):"""Convert specified tree to graphviz instance. IPython can automatically plot the returned graphiz ...
importos os.environ["PATH"] += os.pathsep +'C:/Program Files (x86)/Graphviz2.38/bin/' # 其中C:/Program Files (x86)为安装地址,下载下来的是zip需要解压到这个位置 3.实例代码 def draw_xgboost(self, model): """ this function is able to draw xgboost tree :param model: xgboost model :r...
kwargs : Other keywords passed to graphviz graph_attr Returns --- ax : matplotlib Axes """ import xgboost as xgb if not isinstance(self._df.estimator, xgb.XGBModel): raise ValueError('estimator must be XGBRegressor or XGBClassifier') return xgb.to_graphviz(self._df.estimator, num_trees=...
a custom objective function to be used (see note below). booster: string Specify which booster to use: gbtree, gblinear or dart. nthread : int Number of parallel threads used to run xgboost. (Deprecated, please use ``n_jobs``)