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Subject svn commit: r1618140 - /mahout/site/mahout_cms/trunk/content/users/classification/bankmarketing-example.mdtext
Date Fri, 15 Aug 2014 10:17:33 GMT
Author: frankscholten
Date: Fri Aug 15 10:17:33 2014
New Revision: 1618140

Added bank marketing example.

  (with props)

Added: mahout/site/mahout_cms/trunk/content/users/classification/bankmarketing-example.mdtext
--- mahout/site/mahout_cms/trunk/content/users/classification/bankmarketing-example.mdtext
+++ mahout/site/mahout_cms/trunk/content/users/classification/bankmarketing-example.mdtext
Fri Aug 15 10:17:33 2014
@@ -0,0 +1,47 @@
+Notice:    Licensed to the Apache Software Foundation (ASF) under one
+           or more contributor license agreements.  See the NOTICE file
+           distributed with this work for additional information
+           regarding copyright ownership.  The ASF licenses this file
+           to you under the Apache License, Version 2.0 (the
+           "License"); you may not use this file except in compliance
+           with the License.  You may obtain a copy of the License at
+           .
+           .
+           Unless required by applicable law or agreed to in writing,
+           software distributed under the License is distributed on an
+           KIND, either express or implied.  See the License for the
+           specific language governing permissions and limitations
+           under the License.
+#Bank Marketing Example
+### Introduction
+This page describes how to run Mahout's SGD classifier on the [UCI Bank Marketing dataset](
+The goal is to predict if the client will subscribe a term deposit offered via a phone call.
The features in the dataset consist
+of information such as age, job, marital status as well as information about the last contacts
from the bank.
+### Code & Data
+The bank marketing example code lives under 
+The data can be found at 
+### Code details
+This eaxmple consists of 3 classes:
+  - BankMarketingClassificationMain
+  - TelephoneCall
+  - TelephoneCallParser
+When you run the main method of BankMarketingClassificationMain it parses the dataset using
the TelephoneCallParser and trains
+a logistic regression model with 20 runs and 20 passes. The TelephoneCallParser uses Mahout's
feature vector encoder
+to encode the features in the dataset into a vector. Afterwards the model is tested and the
learning rate and AUC is printed ccuracy is printed to standard output.
\ No newline at end of file

Propchange: mahout/site/mahout_cms/trunk/content/users/classification/bankmarketing-example.mdtext
    svn:eol-style = native

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