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AI实战-加拿大的工业产品价格指数数据集分析预测实例（含4个源代码+18.20 MB完整的数据集） 代码手工整理，无语法错误，可运行。 包括：4个代码，共38.64 KB；数据大小：1个文件共18.20 MB。 使用到的模块： numpy pandas os sklearn.model_selection.train_test_split tensorflow.keras.models.Sequential tensorflow.keras.layers.Dense sklearn.impute.KNNImputer sklearn.impute.IterativeImputer sklearn.linear_model.LinearRegression matplotlib.pyplot sklearn.datasets.make_blobs sklearn.cluster.DBSCAN sklearn.neighbors.LocalOutlierFactor sklearn.ensemble.IsolationForest sklearn.svm.OneClassSVM sklearn.preprocessing.MinMaxScaler sklearn.preprocessing.StandardScaler sklearn.preprocessing.MaxAbsScaler sklearn.preprocessing.RobustScaler sklearn.preprocessing.PowerTransformer sklearn.preprocessing.QuantileTransformer sklearn.preprocessing.OneHotEncoder sklearn.preprocessing.LabelEncoder category_encoders seaborn sklearn.cluster.KMeans sklearn.metrics.silhouette_score sklearn.decomposition.PCA sklearn.datasets.load_iris scipy.cluster.hierarchy.linkage scipy.cluster.hierarchy.dendrogram sklearn.cluster.AgglomerativeClustering sklearn.mixture.GaussianMixture matplotlib warnings sklearn.metrics.mean_squared_error sklearn.metrics.r2_score plotly.express sklearn.ensemble.RandomForestRegressor sklearn.ensemble.GradientBoostingRegressor catboost.CatBoostRegressor sklearn.metrics.mean_absolute_error sklearn.model_selection.RandomizedSearchCV statsmodels.tsa.arima.model.ARIMA