模型训练完成后,我们可以调用训练模型的plot_importance函数来获取特征的重要性。 plt.figure(figsize=(12,6)) lgb.plot_importance(model, max_num_features=30) plt.title("Featurertances") plt.show() 保存feature importance booster = model.booster_ importance = booster.feature_importance(importance_type='...
feature importance #ax = lgb.plot_tree(bst, tree_index=3, figsize=(40, 20), show_info=['split_gain'])ax=lgb.create_tree_digraph(bst)filename='project7-5.png'withopen(filename,'w')asf:f.write(ax._repr_svg_())ax
本教程将详细介绍如何在Python中使用LightGBM进行特征选择与重要性评估,并提供相应的代码示例。加载数据首先,我们需要加载数据集并准备数据用于模型训练。...= lgb_model.feature_importance(importance_type='gain') print("Feature Impor...
feature_importances_:一个数组,形状为[n_features]。如果base_estimator支持,则他给出每个特征的重要性。 oob_score_:一个浮点数,训练数据使用包外...。feature_importances_:一个数组,形状为[n_features]。如果base_estimator支持,则他给出每个特征的重要性。 oob_score_:一个浮点数,训练数据使用包外估计时...
Very simple but it caught me out! The feature importance from gbm = lightgbm.LGBMRegressor() gbm.booster_.feature_importance() is different to gbm.feature_importance() which is scaled to [0, 1]. It would be worth having a note of this in...
模型训练完成后,我们可以调用训练模型的plot_importance函数来获取特征的重要性。 plt.figure(figsize=(12,6)) lgb.plot_importance(model, max_num_features=30) plt.title("Featurertances") plt.show() 保存feature importance booster = model.booster_ ...
模型训练完成后,我们可以调用训练模型的plot_importance函数来获取特征的重要性。 plt.figure(figsize=(12,6)) lgb.plot_importance(model, max_num_features=30) plt.title("Featurertances") plt.show() 保存feature importance booster = model.booster_ ...
Create sskknt·2y ago· 1,577 views arrow_drop_up7 Copy & Edit4 more_vert Copied from private notebook (+78,-332) historyVersion 8 of 8chevron_right Runtime play_arrow 39s Input COMPETITIONS American Express - Default Prediction DATASETS ...
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SummaryPreprocessing / feature engineeringModelLearn and predict with early stoppingFeature importance Competition Notebook Costa Rican Household Poverty Level Prediction Private Score 0.41310 Best Score 0.41975 V1 License This Notebook has been released under the Apache 2.0 open source license. Continue exp...