diff options
Diffstat (limited to 'python/pyspark/mllib/regression.py')
| -rw-r--r-- | python/pyspark/mllib/regression.py | 24 |
1 files changed, 10 insertions, 14 deletions
diff --git a/python/pyspark/mllib/regression.py b/python/pyspark/mllib/regression.py index 266b31d3fa..bc7de6d2e8 100644 --- a/python/pyspark/mllib/regression.py +++ b/python/pyspark/mllib/regression.py @@ -113,10 +113,9 @@ class LinearRegressionWithSGD(object): miniBatchFraction=1.0, initialWeights=None): """Train a linear regression model on the given data.""" sc = data.context - return _regression_train_wrapper(sc, lambda d, i: - sc._jvm.PythonMLLibAPI().trainLinearRegressionModelWithSGD( - d._jrdd, iterations, step, miniBatchFraction, i), - LinearRegressionModel, data, initialWeights) + train_f = lambda d, i: sc._jvm.PythonMLLibAPI().trainLinearRegressionModelWithSGD( + d._jrdd, iterations, step, miniBatchFraction, i) + return _regression_train_wrapper(sc, train_f, LinearRegressionModel, data, initialWeights) class LassoModel(LinearRegressionModelBase): @@ -157,10 +156,9 @@ class LassoWithSGD(object): miniBatchFraction=1.0, initialWeights=None): """Train a Lasso regression model on the given data.""" sc = data.context - return _regression_train_wrapper(sc, lambda d, i: - sc._jvm.PythonMLLibAPI().trainLassoModelWithSGD(d._jrdd, - iterations, step, regParam, miniBatchFraction, i), - LassoModel, data, initialWeights) + train_f = lambda d, i: sc._jvm.PythonMLLibAPI().trainLassoModelWithSGD( + d._jrdd, iterations, step, regParam, miniBatchFraction, i) + return _regression_train_wrapper(sc, train_f, LassoModel, data, initialWeights) class RidgeRegressionModel(LinearRegressionModelBase): @@ -201,18 +199,16 @@ class RidgeRegressionWithSGD(object): miniBatchFraction=1.0, initialWeights=None): """Train a ridge regression model on the given data.""" sc = data.context - return _regression_train_wrapper(sc, lambda d, i: - sc._jvm.PythonMLLibAPI().trainRidgeModelWithSGD(d._jrdd, - iterations, step, regParam, miniBatchFraction, i), - RidgeRegressionModel, data, initialWeights) + train_func = lambda d, i: sc._jvm.PythonMLLibAPI().trainRidgeModelWithSGD( + d._jrdd, iterations, step, regParam, miniBatchFraction, i) + return _regression_train_wrapper(sc, train_func, RidgeRegressionModel, data, initialWeights) def _test(): import doctest globs = globals().copy() globs['sc'] = SparkContext('local[4]', 'PythonTest', batchSize=2) - (failure_count, test_count) = doctest.testmod(globs=globs, - optionflags=doctest.ELLIPSIS) + (failure_count, test_count) = doctest.testmod(globs=globs, optionflags=doctest.ELLIPSIS) globs['sc'].stop() if failure_count: exit(-1) |