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| author | Sean Owen <sowen@cloudera.com> | 2014-07-13 19:27:43 -0700 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2014-07-13 19:27:43 -0700 |
| commit | 635888cbed0e3f4127252fb84db449f0cc9ed659 (patch) | |
| tree | 43433e3393c889f25a8ef4898099664a1a5ce0a7 /docs/mllib-linear-methods.md | |
| parent | 4c8be64e768fe71643b37f1e82f619c8aeac6eff (diff) | |
| download | spark-635888cbed0e3f4127252fb84db449f0cc9ed659.tar.gz spark-635888cbed0e3f4127252fb84db449f0cc9ed659.tar.bz2 spark-635888cbed0e3f4127252fb84db449f0cc9ed659.zip | |
SPARK-2363. Clean MLlib's sample data files
(Just made a PR for this, mengxr was the reporter of:)
MLlib has sample data under serveral folders:
1) data/mllib
2) data/
3) mllib/data/*
Per previous discussion with Matei Zaharia, we want to put them under `data/mllib` and clean outdated files.
Author: Sean Owen <sowen@cloudera.com>
Closes #1394 from srowen/SPARK-2363 and squashes the following commits:
54313dd [Sean Owen] Move ML example data from /mllib/data/ and /data/ into /data/mllib/
Diffstat (limited to 'docs/mllib-linear-methods.md')
| -rw-r--r-- | docs/mllib-linear-methods.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md index 4dfbebbcd0..b4d22e0df5 100644 --- a/docs/mllib-linear-methods.md +++ b/docs/mllib-linear-methods.md @@ -187,7 +187,7 @@ import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLUtils // Load training data in LIBSVM format. -val data = MLUtils.loadLibSVMFile(sc, "mllib/data/sample_libsvm_data.txt") +val data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt") // Split data into training (60%) and test (40%). val splits = data.randomSplit(Array(0.6, 0.4), seed = 11L) @@ -259,7 +259,7 @@ def parsePoint(line): values = [float(x) for x in line.split(' ')] return LabeledPoint(values[0], values[1:]) -data = sc.textFile("mllib/data/sample_svm_data.txt") +data = sc.textFile("data/mllib/sample_svm_data.txt") parsedData = data.map(parsePoint) # Build the model @@ -309,7 +309,7 @@ import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.linalg.Vectors // Load and parse the data -val data = sc.textFile("mllib/data/ridge-data/lpsa.data") +val data = sc.textFile("data/mllib/ridge-data/lpsa.data") val parsedData = data.map { line => val parts = line.split(',') LabeledPoint(parts(0).toDouble, Vectors.dense(parts(1).split(' ').map(_.toDouble))) @@ -356,7 +356,7 @@ def parsePoint(line): values = [float(x) for x in line.replace(',', ' ').split(' ')] return LabeledPoint(values[0], values[1:]) -data = sc.textFile("mllib/data/ridge-data/lpsa.data") +data = sc.textFile("data/mllib/ridge-data/lpsa.data") parsedData = data.map(parsePoint) # Build the model |