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author | Yanbo Liang <ybliang8@gmail.com> | 2015-11-13 08:43:05 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-11-13 08:43:05 -0800 |
commit | 99693fef0a30432d94556154b81872356d921c64 (patch) | |
tree | 09d76cc0ef6cae153718982a9a1ecc827ee12d5f /examples/src/main/python/ml/decision_tree_regression_example.py | |
parent | 61a28486ccbcdd37461419df958aea222c8b9f09 (diff) | |
download | spark-99693fef0a30432d94556154b81872356d921c64.tar.gz spark-99693fef0a30432d94556154b81872356d921c64.tar.bz2 spark-99693fef0a30432d94556154b81872356d921c64.zip |
[SPARK-11723][ML][DOC] Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame
Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame, include:
* Use libSVM data source for all example codes under examples/ml, and remove unused import.
* Use libSVM data source for user guides under ml-*** which were omitted by #8697.
* Fix bug: We should use ```sqlContext.read().format("libsvm").load(path)``` at Java side, but the API doc and user guides misuse as ```sqlContext.read.format("libsvm").load(path)```.
* Code cleanup.
mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9690 from yanboliang/spark-11723.
Diffstat (limited to 'examples/src/main/python/ml/decision_tree_regression_example.py')
-rw-r--r-- | examples/src/main/python/ml/decision_tree_regression_example.py | 5 |
1 files changed, 2 insertions, 3 deletions
diff --git a/examples/src/main/python/ml/decision_tree_regression_example.py b/examples/src/main/python/ml/decision_tree_regression_example.py index 3857aed538..439e398947 100644 --- a/examples/src/main/python/ml/decision_tree_regression_example.py +++ b/examples/src/main/python/ml/decision_tree_regression_example.py @@ -28,7 +28,6 @@ from pyspark.ml import Pipeline from pyspark.ml.regression import DecisionTreeRegressor from pyspark.ml.feature import VectorIndexer from pyspark.ml.evaluation import RegressionEvaluator -from pyspark.mllib.util import MLUtils # $example off$ if __name__ == "__main__": @@ -36,8 +35,8 @@ if __name__ == "__main__": sqlContext = SQLContext(sc) # $example on$ - # Load and parse the data file, converting it to a DataFrame. - data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt").toDF() + # Load the data stored in LIBSVM format as a DataFrame. + data = sqlContext.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") # Automatically identify categorical features, and index them. # We specify maxCategories so features with > 4 distinct values are treated as continuous. |