diff options
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 |