Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/3307#discussion_r20463776
--- Diff: python/pyspark/mllib/classification.py ---
@@ -20,56 +20,106 @@
import numpy
from numpy import array
+from pyspark import RDD
from pyspark.mllib.common import callMLlibFunc
from pyspark.mllib.linalg import SparseVector, _convert_to_vector
from pyspark.mllib.regression import LabeledPoint, LinearModel,
_regression_train_wrapper
-__all__ = ['LogisticRegressionModel', 'LogisticRegressionWithSGD',
'SVMModel',
- 'SVMWithSGD', 'NaiveBayesModel', 'NaiveBayes']
+__all__ = ['LogisticRegressionModel', 'LogisticRegressionWithSGD',
'LogisticRegressionWithLBFGS',
+ 'SVMModel', 'SVMWithSGD', 'NaiveBayesModel', 'NaiveBayes']
-class LogisticRegressionModel(LinearModel):
+class ClassificationModel(LinearModel):
--- End diff --
The setThreshold methods don't seem to be in Classification in Scala, so I
don't think we should have them here. They are on LogisticRegressionModel and
SVMModel but it's not clear that all classification models will have a
threshold.
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