From ba6bd707867f18ba1708dc30e4ce7dc2f1425055 Mon Sep 17 00:00:00 2001 From: zero323 Date: Tue, 24 Nov 2020 14:06:59 +0100 Subject: [PATCH] Address virya's notes --- python/pyspark/mllib/classification.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/python/pyspark/mllib/classification.py b/python/pyspark/mllib/classification.py index 0a508f112df33..bd43e91afd280 100644 --- a/python/pyspark/mllib/classification.py +++ b/python/pyspark/mllib/classification.py @@ -97,7 +97,7 @@ class LogisticRegressionModel(LinearClassificationModel): intercept : float Intercept computed for this model. (Only used in Binary Logistic Regression. In Multinomial Logistic Regression, the intercepts will - not bea single value, so the intercepts will be part of the + not be a single value, so the intercepts will be part of the weights.) numFeatures : int The dimension of the features. @@ -292,7 +292,7 @@ def train(cls, data, iterations=100, step=1.0, miniBatchFraction=1.0, step : float, optional The step parameter used in SGD. (default: 1.0) - miniBatchFraction: float, optional + miniBatchFraction : float, optional Fraction of data to be used for each SGD iteration. (default: 1.0) initialWeights : :py:class:`pyspark.mllib.linalg.Vector` or convertible, optional @@ -552,7 +552,7 @@ def train(cls, data, iterations=100, step=1.0, regParam=0.01, regParam : float, optional The regularizer parameter. (default: 0.01) - miniBatchFraction: float, optional + miniBatchFraction : float, optional Fraction of data to be used for each SGD iteration. (default: 1.0) initialWeights : :py:class:`pyspark.mllib.linalg.Vector` or convertible, optional