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pyLDAvis 模块代码及应用. 背景. pyLDAvis模块是python中的一个对LDA主题模型算法的可视化模块。本文的代码是根据github上的某个项目代码修改而得,很感谢github及创造原始代码的大牛朋友们! A benefit of using ensembles of decision tree methods like gradient boosting is that they can automatically provide estimates of feature importance from a trained predictive model. In this post you will discover how you can estimate the importance of features for a predictive modeling problem using the XGBoost library in Python. After reading this […] class _H2OBaseUnivariateSelector (six. with_metaclass (ABCMeta, BaseH2OFeatureSelector)): """The base class for all univariate feature selectors in H2O. Parameters-----feature_names : array_like (str), optional (default=None) The list of names on which to fit the transformer. target_feature : str, optional (default=None) The name of the target feature (is excluded from the fit) for the ...