sklearn模块基础实战

weiweitech 2023-01-12 23:27:28

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sklearn模块基础实战

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AI实战-信用卡客户基础数据分析预测实例（含20个源代码+1.44 MB完整的数据集）代码手工整理，无语法错误，可运行。包括：20个代码，共219.44 KB；数据大小：1个文件共1.44 MB。使用到的模块： numpy pandas warnings matplotlib.pyplot seaborn matplotlib.font_manager matplotlib.ticker.FuncFormatter sklearn.impute.SimpleImputer sklearn.ensemble.RandomForestClassifier sklearn.feature_selection.SelectFromModel sklearn.preprocessing.StandardScaler sklearn.model_selection.train_test_split sklearn.metrics.( os imblearn.over_sampling.ADASYN torch pytorch_tabnet.tab_model.TabNetClassifier sklearn.metrics.accuracy_score torch.nn tab_transformer_pytorch.TabTransformer tqdm.tqdm tab_transformer_pytorch.FTTransformer sklearn.metrics.classification_report sklearn.metrics.confusion_matrix sklearn.metrics.precision_recall_curve plotly.offline.plot plotly.offline.iplot plotly.graph_objs cufflinks plotly.express imblearn.over_sampling.RandomOverSampler sklearn.neighbors.KNeighborsClassifier sklearn.preprocessing.MinMaxScaler sklearn.decomposition.PCA sklearn.linear_model.LogisticRegression sklearn.svm.SVC sklearn.tree.DecisionTreeClassifier sklearn.tree.plot_tree sklearn.naive_bayes.GaussianNB sklearn.naive_bayes.MultinomialNB sklearn.linear_model.LinearRegression sklearn.linear_model.Ridge sklearn.linear_model.Lasso sklearn.linear_model.ElasticNet sklearn.svm.SVR sklearn.tree.DecisionTreeRegressor sklearn.ensemble.RandomForestRegressor sklearn.ensemble.GradientBoostingRegressor sklearn.metrics.mean_absolute_error sklearn.metrics.median_absolute_error sklearn.metrics.mean_squared_error sklearn.metrics.r2_score sklearn.cluster.KMeans xgboost sklearn.metrics.ConfusionMatrixDisplay sklearn.metrics.roc_auc_score sklearn.metrics.roc_curve sklearn.metrics.auc matplotlib imblearn.over_sampling.SMOTE xgboost.XGBClassifier sklearn.preprocessing.LabelEncoder sklearn.model_selection.StratifiedKFold sklearn.model_selection.GridSearchCV imblearn.under_sampling.RandomUnderSampler sklearn.metrics pickle math sklearn.cluster.AgglomerativeClustering scipy.cluster.hierarchy sklearn.nei

AI实战-高中学生基础信息数据集分析预测实例（含20个源代码+162.99 KB完整的数据集）代码手工整理，无语法错误，可运行。包括：20个代码，共101.77 KB；数据大小：1个文件共162.99 KB。使用到的模块： numpy pandas matplotlib.pyplot ydata_profiling.ProfileReport sklearn.model_selection.train_test_split sklearn.model_selection.cross_val_score sklearn.compose.ColumnTransformer sklearn.pipeline.Pipeline sklearn.preprocessing.StandardScaler sklearn.impute.SimpleImputer sklearn.linear_model.LinearRegression sklearn.linear_model.Ridge sklearn.linear_model.Lasso sklearn.ensemble.RandomForestRegressor sklearn.metrics.mean_squared_error sklearn.metrics.r2_score joblib sklearn.metrics.accuracy_score sklearn.linear_model.LogisticRegression sklearn.ensemble.RandomForestClassifier xgboost.XGBClassifier lightgbm.LGBMClassifier catboost.CatBoostClassifier sklearn.metrics.mean_absolute_error warnings torch torch.nn torch.optim seaborn sklearn.tree.DecisionTreeClassifier sklearn.svm.SVC sklearn.neighbors.KNeighborsClassifier matplotlib.patches.PathPatch matplotlib.path.Path plotly.graph_objects os plotly.express sklearn.metrics.confusion_matrix sklearn.ensemble.GradientBoostingClassifier sklearn.ensemble.AdaBoostClassifier sklearn.naive_bayes.GaussianNB sklearn.preprocessing.LabelEncoder sklearn.model_selection.RepeatedStratifiedKFold sklearn.model_selection.GridSearchCV catboost.cv scipy.stats sklearn.metrics.classification_report sklearn.metrics.f1_score sklearn.tree.DecisionTreeRegressor xgboost sklearn.pipeline.make_pipeline sklearn.model_selection.validation_curve sklearn.preprocessing.PolynomialFeatures scipy.stats.levene scipy.stats.kruskal scipy.stats.shapiro scipy.stats.ttest_ind sklearn.tree.plot_tree sklearn.tree.export_text

Python数据分析案例实战-教学大纲.docx

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