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author | Shivaram Venkataraman <shivaram@eecs.berkeley.edu> | 2013-08-13 16:55:53 -0700 |
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committer | Shivaram Venkataraman <shivaram@eecs.berkeley.edu> | 2013-08-13 16:55:53 -0700 |
commit | c874625354de7117da9586cfbbe919bb6801a932 (patch) | |
tree | 14e1ffee5098b15273035f5784c89e02a41fde12 | |
parent | 0ab6ff4c3252e7cb9ea573e09d9188da1fcb87cc (diff) | |
download | spark-c874625354de7117da9586cfbbe919bb6801a932.tar.gz spark-c874625354de7117da9586cfbbe919bb6801a932.tar.bz2 spark-c874625354de7117da9586cfbbe919bb6801a932.zip |
Specify label format in LogisticRegression.
-rw-r--r-- | mllib/src/main/scala/spark/mllib/classification/LogisticRegression.scala | 6 |
1 files changed, 6 insertions, 0 deletions
diff --git a/mllib/src/main/scala/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/spark/mllib/classification/LogisticRegression.scala index 7f0b1ba841..474ca6e97c 100644 --- a/mllib/src/main/scala/spark/mllib/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/spark/mllib/classification/LogisticRegression.scala @@ -48,6 +48,7 @@ class LogisticRegressionModel( /** * Train a classification model for Logistic Regression using Stochastic Gradient Descent. + * NOTE: Labels used in Logistic Regression should be {0, 1} */ class LogisticRegressionWithSGD private ( var stepSize: Double, @@ -79,6 +80,7 @@ class LogisticRegressionWithSGD private ( /** * Top-level methods for calling Logistic Regression. + * NOTE: Labels used in Logistic Regression should be {0, 1} */ object LogisticRegressionWithSGD { // NOTE(shivaram): We use multiple train methods instead of default arguments to support @@ -89,6 +91,7 @@ object LogisticRegressionWithSGD { * number of iterations of gradient descent using the specified step size. Each iteration uses * `miniBatchFraction` fraction of the data to calculate the gradient. The weights used in * gradient descent are initialized using the initial weights provided. + * NOTE: Labels used in Logistic Regression should be {0, 1} * * @param input RDD of (label, array of features) pairs. * @param numIterations Number of iterations of gradient descent to run. @@ -113,6 +116,7 @@ object LogisticRegressionWithSGD { * Train a logistic regression model given an RDD of (label, features) pairs. We run a fixed * number of iterations of gradient descent using the specified step size. Each iteration uses * `miniBatchFraction` fraction of the data to calculate the gradient. + * NOTE: Labels used in Logistic Regression should be {0, 1} * * @param input RDD of (label, array of features) pairs. * @param numIterations Number of iterations of gradient descent to run. @@ -135,6 +139,7 @@ object LogisticRegressionWithSGD { * Train a logistic regression model given an RDD of (label, features) pairs. We run a fixed * number of iterations of gradient descent using the specified step size. We use the entire data * set to update the gradient in each iteration. + * NOTE: Labels used in Logistic Regression should be {0, 1} * * @param input RDD of (label, array of features) pairs. * @param stepSize Step size to be used for each iteration of Gradient Descent. @@ -155,6 +160,7 @@ object LogisticRegressionWithSGD { * Train a logistic regression model given an RDD of (label, features) pairs. We run a fixed * number of iterations of gradient descent using a step size of 1.0. We use the entire data set * to update the gradient in each iteration. + * NOTE: Labels used in Logistic Regression should be {0, 1} * * @param input RDD of (label, array of features) pairs. * @param numIterations Number of iterations of gradient descent to run. |