[ https://issues.apache.org/jira/browse/SPARK-13443?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Stephanie Bodoff updated SPARK-13443: ------------------------------------- Attachment: Screen Shot 2016-02-22 at 5.09.30 PM.png > MLlib documentation displays Math Processing Error > -------------------------------------------------- > > Key: SPARK-13443 > URL: https://issues.apache.org/jira/browse/SPARK-13443 > Project: Spark > Issue Type: Bug > Components: Documentation > Reporter: Stephanie Bodoff > Attachments: Screen Shot 2016-02-22 at 5.09.30 PM.png > > > http://spark.apache.org/docs/latest/mllib-linear-methods.html > Many standard machine learning methods can be formulated as a convex > optimization problem, i.e. the task of finding a minimizer of a convex > function [Math Processing Error] that depends on a variable vector [Math > Processing Error] (called weights in the code), which has [Math Processing > Error] entries. Formally, we can write this as the optimization problem [Math > Processing Error], where the objective function is of the form [Math > Processing Error] Here the vectors [Math Processing Error] are the training > data examples, for [Math Processing Error], and [Math Processing Error] are > their corresponding labels, which we want to predict. We call the method > linear if [Math Processing Error] can be expressed as a function of [Math > Processing Error] and [Math Processing Error]. Several of spark.mllib’s > classification and regression algorithms fall into this category, and are > discussed here. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org