Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8518#discussion_r38268904
--- Diff: docs/ml-guide.md ---
@@ -340,28 +325,23 @@ for (Row r: results.select("features", "label",
"myProbability", "prediction").c
+ ", prediction=" + r.get(3));
}
-jsc.stop();
{% endhighlight %}
</div>
<div data-lang="python">
{% highlight python %}
-from pyspark import SparkContext
-from pyspark.mllib.regression import LabeledPoint
+from pyspark.mllib.linalg import Vectors
from pyspark.ml.classification import LogisticRegression
from pyspark.ml.param import Param, Params
-from pyspark.sql import Row, SQLContext
-
-sc = SparkContext(appName="SimpleParamsExample")
-sqlContext = SQLContext(sc)
# Prepare training data.
# We use LabeledPoint.
-# Spark SQL can convert RDDs of LabeledPoints into DataFrames.
-training = sc.parallelize([LabeledPoint(1.0, [0.0, 1.1, 0.1]),
- LabeledPoint(0.0, [2.0, 1.0, -1.0]),
- LabeledPoint(0.0, [2.0, 1.3, 1.0]),
- LabeledPoint(1.0, [0.0, 1.2, -0.5])])
+# Spark SQL can convert a list of LabeledPoints into DataFrames.
--- End diff --
okay
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