uiClimber使用手册手机依赖「uiClimber使用手册」

AI实战-营销活动和数据集分析预测实例（含19个源代码+523.50 KB完整的数据集） 代码手工整理，无语法错误，可运行。 包括：19个代码，共231.67 KB；数据大小：2个文件共523.50 KB。 使用到的模块： pandas numpy seaborn matplotlib matplotlib.pyplot warnings sklearn.model_selection.train_test_split sklearn.ensemble.RandomForestClassifier sklearn.metrics.accuracy_score sklearn.metrics.confusion_matrix scipy.stats pingouin datetime.date matplotlib.ticker.PercentFormatter scipy.stats.f_oneway scipy.stats.friedmanchisquare sklearn.linear_model.LogisticRegression sklearn.metrics.precision_score sklearn.metrics.recall_score sklearn.metrics.f1_score sklearn.metrics.classification_report sklearn.metrics.roc_curve sklearn.metrics.roc_auc_score sklearn.svm sklearn.cluster.KMeans sklearn.preprocessing.StandardScaler sklearn.decomposition.PCA sklearn.metrics.silhouette_score sklearn.metrics.davies_bouldin_score sklearn.preprocessing.MinMaxScaler IPython.display.display sklearn.preprocessing.OneHotEncoder sklearn.model_selection.GridSearchCV sklearn.tree.DecisionTreeClassifier sklearn.tree.plot_tree sklearn.ensemble.GradientBoostingClassifier sklearn.metrics.RocCurveDisplay imblearn.over_sampling.SMOTE imblearn.pipeline.Pipeline sklearn.model_selection.RandomizedSearchCV sklearn.model_selection.StratifiedKFold sklearn.feature_selection.RFE sklearn.utils.class_weight sklearn.feature_selection.RFECV plotly.express datetime xgboost.XGBClassifier xgboost.plot_importance os sklearn.preprocessing.LabelEncoder kneed.KneeLocator sklearn.linear_model.LinearRegression sklearn.metrics.mean_squared_error sklearn.metrics.r2_score lightgbm.LGBMRegressor tensorflow sklearn.base.BaseEstimator sklearn.base.TransformerMixin sklearn.model_selection.cross_val_score sklearn.metrics.precision_recall_fscore_support xgboost datetime.datetime sklearn.metrics.ConfusionMatrixDisplay sklearn.tree.export_text missingno plotly.offline.init_notebook_mode