From c74d38fd8faf8cba981cf934341d24b9a3167025 Mon Sep 17 00:00:00 2001
From: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Date: Thu, 17 Sep 2015 08:50:46 -0700
Subject: [PATCH] [SPARK-10274] [MLLIB] Add @since annotation to
pyspark.mllib.fpm
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #8665 from yu-iskw/SPARK-10274.
---
python/pyspark/mllib/fpm.py | 10 +++++++++-
1 file changed, 9 insertions(+), 1 deletion(-)
diff --git a/python/pyspark/mllib/fpm.py b/python/pyspark/mllib/fpm.py
index bdc4a132b1..bdabba9602 100644
--- a/python/pyspark/mllib/fpm.py
+++ b/python/pyspark/mllib/fpm.py
@@ -19,7 +19,7 @@ import numpy
from numpy import array
from collections import namedtuple
-from pyspark import SparkContext
+from pyspark import SparkContext, since
from pyspark.rdd import ignore_unicode_prefix
from pyspark.mllib.common import JavaModelWrapper, callMLlibFunc, inherit_doc
@@ -41,8 +41,11 @@ class FPGrowthModel(JavaModelWrapper):
>>> model = FPGrowth.train(rdd, 0.6, 2)
>>> sorted(model.freqItemsets().collect())
[FreqItemset(items=[u'a'], freq=4), FreqItemset(items=[u'c'], freq=3), ...
+
+ .. versionadded:: 1.4.0
"""
+ @since("1.4.0")
def freqItemsets(self):
"""
Returns the frequent itemsets of this model.
@@ -55,9 +58,12 @@ class FPGrowth(object):
.. note:: Experimental
A Parallel FP-growth algorithm to mine frequent itemsets.
+
+ .. versionadded:: 1.4.0
"""
@classmethod
+ @since("1.4.0")
def train(cls, data, minSupport=0.3, numPartitions=-1):
"""
Computes an FP-Growth model that contains frequent itemsets.
@@ -74,6 +80,8 @@ class FPGrowth(object):
class FreqItemset(namedtuple("FreqItemset", ["items", "freq"])):
"""
Represents an (items, freq) tuple.
+
+ .. versionadded:: 1.4.0
"""
--
GitLab