diff options
Diffstat (limited to 'python/pyspark/ml')
| -rw-r--r-- | python/pyspark/ml/classification.py | 4 | ||||
| -rwxr-xr-x | python/pyspark/ml/feature.py | 2 | ||||
| -rw-r--r-- | python/pyspark/ml/recommendation.py | 4 | ||||
| -rw-r--r-- | python/pyspark/ml/regression.py | 4 |
4 files changed, 7 insertions, 7 deletions
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py index a3cd91790c..e86c27ecaf 100644 --- a/python/pyspark/ml/classification.py +++ b/python/pyspark/ml/classification.py @@ -685,7 +685,7 @@ class RandomForestClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred self._java_obj = self._new_java_obj( "org.apache.spark.ml.classification.RandomForestClassifier", self.uid) self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, - maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, seed=None, + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="gini", numTrees=20, featureSubsetStrategy="auto") kwargs = self.__init__._input_kwargs self.setParams(**kwargs) @@ -825,7 +825,7 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol "org.apache.spark.ml.classification.GBTClassifier", self.uid) self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, - lossType="logistic", maxIter=20, stepSize=0.1, seed=None) + lossType="logistic", maxIter=20, stepSize=0.1) kwargs = self.__init__._input_kwargs self.setParams(**kwargs) diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 1e9ec0fbb4..bbbb94f9a0 100755 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -2260,7 +2260,7 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has super(Word2Vec, self).__init__() self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.Word2Vec", self.uid) self._setDefault(vectorSize=100, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, - seed=None, windowSize=5, maxSentenceLength=1000) + windowSize=5, maxSentenceLength=1000) kwargs = self.__init__._input_kwargs self.setParams(**kwargs) diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py index 0a7096794d..e28d38bd19 100644 --- a/python/pyspark/ml/recommendation.py +++ b/python/pyspark/ml/recommendation.py @@ -68,7 +68,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha >>> df = spark.createDataFrame( ... [(0, 0, 4.0), (0, 1, 2.0), (1, 1, 3.0), (1, 2, 4.0), (2, 1, 1.0), (2, 2, 5.0)], ... ["user", "item", "rating"]) - >>> als = ALS(rank=10, maxIter=5) + >>> als = ALS(rank=10, maxIter=5, seed=0) >>> model = als.fit(df) >>> model.rank 10 @@ -142,7 +142,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha super(ALS, self).__init__() self._java_obj = self._new_java_obj("org.apache.spark.ml.recommendation.ALS", self.uid) self._setDefault(rank=10, maxIter=10, regParam=0.1, numUserBlocks=10, numItemBlocks=10, - implicitPrefs=False, alpha=1.0, userCol="user", itemCol="item", seed=None, + implicitPrefs=False, alpha=1.0, userCol="user", itemCol="item", ratingCol="rating", nonnegative=False, checkpointInterval=10, intermediateStorageLevel="MEMORY_AND_DISK", finalStorageLevel="MEMORY_AND_DISK") diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index 8d2378d51f..29efd6a852 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -894,7 +894,7 @@ class RandomForestRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi "org.apache.spark.ml.regression.RandomForestRegressor", self.uid) self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, - impurity="variance", subsamplingRate=1.0, seed=None, numTrees=20, + impurity="variance", subsamplingRate=1.0, numTrees=20, featureSubsetStrategy="auto") kwargs = self.__init__._input_kwargs self.setParams(**kwargs) @@ -1023,7 +1023,7 @@ class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, subsamplingRate=1.0, checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, - seed=None, impurity="variance") + impurity="variance") kwargs = self.__init__._input_kwargs self.setParams(**kwargs) |