Logistic Regression (MAHOUT) edited by Isabel Drost
Page:
http://cwiki.apache.org/confluence/display/MAHOUT/Logistic+Regression
Changes:
http://cwiki.apache.org/confluence/pages/diffpagesbyversion.action?pageId=75687&originalVersion=3&revisedVersion=4
Comment:
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added link to thesis paper describing logReg
Change summary:
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added link to thesis paper describing logReg
Change summary:
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added link to thesis paper describing logReg
Change summary:
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added link to thesis paper describing logReg
Change summary:
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added link to thesis paper describing logReg
Content:
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h1. Logistic Regression
Logistic regression is a model used for prediction of the probability of
occurrence of an event. It makes use of several predictor variables that may be
either numerical or categories.
Logistic regression is the discrimitive equivalent to naive bayes. It does not
model the probability of the input data (p( x )) as naive bayes does.
Accordingly it cannot make false assumptions on the distribution of the input
data, as is done in naive bayes.
For a more detailed analysis of the approach, have a look at the thesis of Paul
Komarek:
http://www.autonlab.org/autonweb/14709/version/4/part/5/data/komarek:lr_thesis.pdf?branch=main&language=en
h2. Parallelization strategy
h2. Design of packages
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