Return-Path: X-Original-To: apmail-spark-commits-archive@minotaur.apache.org Delivered-To: apmail-spark-commits-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id A10C618D46 for ; Mon, 8 Feb 2016 19:06:42 +0000 (UTC) Received: (qmail 14621 invoked by uid 500); 8 Feb 2016 19:06:42 -0000 Delivered-To: apmail-spark-commits-archive@spark.apache.org Received: (qmail 14595 invoked by uid 500); 8 Feb 2016 19:06:42 -0000 Mailing-List: contact commits-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list commits@spark.apache.org Received: (qmail 14586 invoked by uid 99); 8 Feb 2016 19:06:42 -0000 Received: from git1-us-west.apache.org (HELO git1-us-west.apache.org) (140.211.11.23) by apache.org (qpsmtpd/0.29) with ESMTP; Mon, 08 Feb 2016 19:06:42 +0000 Received: by git1-us-west.apache.org (ASF Mail Server at git1-us-west.apache.org, from userid 33) id 69485E00A0; Mon, 8 Feb 2016 19:06:42 +0000 (UTC) Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit From: meng@apache.org To: commits@spark.apache.org Message-Id: X-Mailer: ASF-Git Admin Mailer Subject: spark git commit: [SPARK-12986][DOC] Fix pydoc warnings in mllib/regression.py Date: Mon, 8 Feb 2016 19:06:42 +0000 (UTC) Repository: spark Updated Branches: refs/heads/master 140ddef37 -> edf4a0e62 [SPARK-12986][DOC] Fix pydoc warnings in mllib/regression.py I have fixed the warnings by running "make html" under "python/docs/". They are caused by not having blank lines around indented paragraphs. Author: Nam Pham Closes #11025 from nampham2/SPARK-12986. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/edf4a0e6 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/edf4a0e6 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/edf4a0e6 Branch: refs/heads/master Commit: edf4a0e62e6fdb849cca4f23a7060da5ec782b07 Parents: 140ddef Author: Nam Pham Authored: Mon Feb 8 11:06:41 2016 -0800 Committer: Xiangrui Meng Committed: Mon Feb 8 11:06:41 2016 -0800 ---------------------------------------------------------------------- python/pyspark/mllib/regression.py | 34 ++++++++++++++++++++------------- 1 file changed, 21 insertions(+), 13 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/edf4a0e6/python/pyspark/mllib/regression.py ---------------------------------------------------------------------- diff --git a/python/pyspark/mllib/regression.py b/python/pyspark/mllib/regression.py index 13b3397..4dd7083 100644 --- a/python/pyspark/mllib/regression.py +++ b/python/pyspark/mllib/regression.py @@ -219,8 +219,10 @@ class LinearRegressionWithSGD(object): """ Train a linear regression model with no regularization using Stochastic Gradient Descent. This solves the least squares regression formulation - f(weights) = 1/n ||A weights-y||^2^ - (which is the mean squared error). + + f(weights) = 1/n ||A weights-y||^2 + + which is the mean squared error. Here the data matrix has n rows, and the input RDD holds the set of rows of A, each with its corresponding right hand side label y. See also the documentation for the precise formulation. @@ -367,8 +369,10 @@ class LassoModel(LinearRegressionModelBase): class LassoWithSGD(object): """ Train a regression model with L1-regularization using Stochastic Gradient Descent. - This solves the l1-regularized least squares regression formulation - f(weights) = 1/2n ||A weights-y||^2^ + regParam ||weights||_1 + This solves the L1-regularized least squares regression formulation + + f(weights) = 1/2n ||A weights-y||^2 + regParam ||weights||_1 + Here the data matrix has n rows, and the input RDD holds the set of rows of A, each with its corresponding right hand side label y. See also the documentation for the precise formulation. @@ -505,8 +509,10 @@ class RidgeRegressionModel(LinearRegressionModelBase): class RidgeRegressionWithSGD(object): """ Train a regression model with L2-regularization using Stochastic Gradient Descent. - This solves the l2-regularized least squares regression formulation - f(weights) = 1/2n ||A weights-y||^2^ + regParam/2 ||weights||^2^ + This solves the L2-regularized least squares regression formulation + + f(weights) = 1/2n ||A weights-y||^2 + regParam/2 ||weights||^2 + Here the data matrix has n rows, and the input RDD holds the set of rows of A, each with its corresponding right hand side label y. See also the documentation for the precise formulation. @@ -655,17 +661,19 @@ class IsotonicRegression(object): Only univariate (single feature) algorithm supported. Sequential PAV implementation based on: - Tibshirani, Ryan J., Holger Hoefling, and Robert Tibshirani. + + Tibshirani, Ryan J., Holger Hoefling, and Robert Tibshirani. "Nearly-isotonic regression." Technometrics 53.1 (2011): 54-61. - Available from [[http://www.stat.cmu.edu/~ryantibs/papers/neariso.pdf]] + Available from http://www.stat.cmu.edu/~ryantibs/papers/neariso.pdf Sequential PAV parallelization based on: - Kearsley, Anthony J., Richard A. Tapia, and Michael W. Trosset. - "An approach to parallelizing isotonic regression." - Applied Mathematics and Parallel Computing. Physica-Verlag HD, 1996. 141-147. - Available from [[http://softlib.rice.edu/pub/CRPC-TRs/reports/CRPC-TR96640.pdf]] - @see [[http://en.wikipedia.org/wiki/Isotonic_regression Isotonic regression (Wikipedia)]] + Kearsley, Anthony J., Richard A. Tapia, and Michael W. Trosset. + "An approach to parallelizing isotonic regression." + Applied Mathematics and Parallel Computing. Physica-Verlag HD, 1996. 141-147. + Available from http://softlib.rice.edu/pub/CRPC-TRs/reports/CRPC-TR96640.pdf + + See `Isotonic regression (Wikipedia) `_. .. versionadded:: 1.4.0 """ --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscribe@spark.apache.org For additional commands, e-mail: commits-help@spark.apache.org