dimensional metals, inc. specializes in the manufacturing of architectural metal panel systems and fabricated architectural sheet metal for the construciton industry.
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Installing scikit-learn — scikit-learn 1. 7. 2 documentation The Debian Ubuntu package is split in three different packages called python3-sklearn (python modules), python3-sklearn-lib (low-level implementations and bindings), python-sklearn-doc (documentation)
Getting Started — scikit-learn 1. 7. 2 documentation >>> from sklearn preprocessing import StandardScaler >>> X = [[0, 15], [1, -10]] >>> # scale data according to computed scaling values >>> StandardScaler() fit(X) transform(X) array([[-1 , 1 ], [ 1 , -1 ]])
User Guide — scikit-learn 1. 7. 2 documentation Supervised learning- Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, Or
1. Supervised learning — scikit-learn 1. 7. 2 documentation Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, Orthogonal Matching Pur
LinearRegression — scikit-learn 1. 7. 2 documentation Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn set_config)
RandomForestRegressor — scikit-learn 1. 7. 2 documentation Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn set_config)