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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 /docs/ml-linear-methods.md | |
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 'docs/ml-linear-methods.md')
-rw-r--r-- | docs/ml-linear-methods.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/ml-linear-methods.md b/docs/ml-linear-methods.md index 16e2ee7129..85edfd3734 100644 --- a/docs/ml-linear-methods.md +++ b/docs/ml-linear-methods.md @@ -95,7 +95,7 @@ public class LogisticRegressionWithElasticNetExample { String path = "data/mllib/sample_libsvm_data.txt"; // Load training data - DataFrame training = sqlContext.read.format("libsvm").load(path); + DataFrame training = sqlContext.read().format("libsvm").load(path); LogisticRegression lr = new LogisticRegression() .setMaxIter(10) @@ -292,7 +292,7 @@ public class LinearRegressionWithElasticNetExample { String path = "data/mllib/sample_libsvm_data.txt"; // Load training data - DataFrame training = sqlContext.read.format("libsvm").load(path); + DataFrame training = sqlContext.read().format("libsvm").load(path); LinearRegression lr = new LinearRegression() .setMaxIter(10) |