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-rw-r--r--examples/src/main/python/ml/simple_text_classification_pipeline.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/examples/src/main/python/ml/simple_text_classification_pipeline.py b/examples/src/main/python/ml/simple_text_classification_pipeline.py
index fab21f003b..b4f06bf888 100644
--- a/examples/src/main/python/ml/simple_text_classification_pipeline.py
+++ b/examples/src/main/python/ml/simple_text_classification_pipeline.py
@@ -48,7 +48,7 @@ if __name__ == "__main__":
# Configure an ML pipeline, which consists of tree stages: tokenizer, hashingTF, and lr.
tokenizer = Tokenizer(inputCol="text", outputCol="words")
hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol="features")
- lr = LogisticRegression(maxIter=10, regParam=0.01)
+ lr = LogisticRegression(maxIter=10, regParam=0.001)
pipeline = Pipeline(stages=[tokenizer, hashingTF, lr])
# Fit the pipeline to training documents.
@@ -58,7 +58,7 @@ if __name__ == "__main__":
Document = Row("id", "text")
test = sc.parallelize([(4, "spark i j k"),
(5, "l m n"),
- (6, "mapreduce spark"),
+ (6, "spark hadoop spark"),
(7, "apache hadoop")]) \
.map(lambda x: Document(*x)).toDF()