diff options
Diffstat (limited to 'python/pyspark/mllib/__init__.py')
-rw-r--r-- | python/pyspark/mllib/__init__.py | 34 |
1 files changed, 8 insertions, 26 deletions
diff --git a/python/pyspark/mllib/__init__.py b/python/pyspark/mllib/__init__.py index 6037a3aa63..e9c62f3410 100644 --- a/python/pyspark/mllib/__init__.py +++ b/python/pyspark/mllib/__init__.py @@ -16,31 +16,13 @@ # """ -PySpark is the Python API for Spark. - -Public classes: - - - L{SparkContext<pyspark.context.SparkContext>} - Main entry point for Spark functionality. - - L{RDD<pyspark.rdd.RDD>} - A Resilient Distributed Dataset (RDD), the basic abstraction in Spark. - - L{Broadcast<pyspark.broadcast.Broadcast>} - A broadcast variable that gets reused across tasks. - - L{Accumulator<pyspark.accumulators.Accumulator>} - An "add-only" shared variable that tasks can only add values to. - - L{SparkFiles<pyspark.files.SparkFiles>} - Access files shipped with jobs. - - L{StorageLevel<pyspark.storagelevel.StorageLevel>} - Finer-grained cache persistence levels. +Python bindings for MLlib. """ -import sys -import os -sys.path.insert(0, os.path.join(os.environ["SPARK_HOME"], "python/lib/py4j0.7.egg")) - -from pyspark.mllib.regression import LinearRegressionModel, LassoModel, RidgeRegressionModel, LinearRegressionWithSGD, LassoWithSGD, RidgeRegressionWithSGD -from pyspark.mllib.classification import LogisticRegressionModel, SVMModel, LogisticRegressionWithSGD, SVMWithSGD -from pyspark.mllib.recommendation import MatrixFactorizationModel, ALS -from pyspark.mllib.clustering import KMeansModel, KMeans - -__all__ = ["LinearRegressionModel", "LassoModel", "RidgeRegressionModel", "LinearRegressionWithSGD", "LassoWithSGD", "RidgeRegressionWithSGD", "LogisticRegressionModel", "SVMModel", "LogisticRegressionWithSGD", "SVMWithSGD", "MatrixFactorizationModel", "ALS", "KMeansModel", "KMeans"] +#from pyspark.mllib.regression import LinearRegressionModel, LassoModel, RidgeRegressionModel, LinearRegressionWithSGD, LassoWithSGD, RidgeRegressionWithSGD +#from pyspark.mllib.classification import LogisticRegressionModel, SVMModel, LogisticRegressionWithSGD, SVMWithSGD +#from pyspark.mllib.recommendation import MatrixFactorizationModel, ALS +#from pyspark.mllib.clustering import KMeansModel, KMeans +# +# +#__all__ = ["LinearRegressionModel", "LassoModel", "RidgeRegressionModel", "LinearRegressionWithSGD", "LassoWithSGD", "RidgeRegressionWithSGD", "LogisticRegressionModel", "SVMModel", "LogisticRegressionWithSGD", "SVMWithSGD", "MatrixFactorizationModel", "ALS", "KMeansModel", "KMeans"] |