| # |
| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| """ |
| DataFrame-based machine learning APIs to let users quickly assemble and configure practical |
| machine learning pipelines. |
| """ |
| from pyspark.ml.base import ( |
| Estimator, |
| Model, |
| Predictor, |
| PredictionModel, |
| Transformer, |
| UnaryTransformer, |
| ) |
| from pyspark.ml.pipeline import Pipeline, PipelineModel |
| from pyspark.ml import ( |
| classification, |
| clustering, |
| evaluation, |
| feature, |
| fpm, |
| image, |
| recommendation, |
| regression, |
| stat, |
| tuning, |
| util, |
| linalg, |
| param, |
| ) |
| from pyspark.ml.torch.distributor import TorchDistributor |
| |
| __all__ = [ |
| "Transformer", |
| "UnaryTransformer", |
| "Estimator", |
| "Model", |
| "Predictor", |
| "PredictionModel", |
| "Pipeline", |
| "PipelineModel", |
| "classification", |
| "clustering", |
| "evaluation", |
| "feature", |
| "fpm", |
| "image", |
| "recommendation", |
| "regression", |
| "stat", |
| "tuning", |
| "util", |
| "linalg", |
| "param", |
| "TorchDistributor", |
| ] |