- General
- Developers
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- Algorithms
- List of algorithms
- Distributed Matrix Decomposition
- Cholesky QR
- SSVD
- Distributed ALS
- SPCA
- Recommendations
- Recommender Overview
- Intro to cooccurrence-based
recommendations with Spark - Classification
- Spark Naive Bayes
- MapReduce Basics
- List of algorithms
- Overview
- Working with text
- Creating vectors from text
- Collocations
- Dimensionality reduction
- Singular Value Decomposition
- Stochastic SVD
- Topic Models
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- Mahout MapReduce
- Classification
- Naive Bayes
- Hidden Markov Models
- Logistic Regression (Single Machine)
- Random Forest
- Classification Examples
- Breiman example
- 20 newsgroups example
- SGD classifier bank marketing
- Wikipedia XML parser and classifier
- Clustering
- k-Means
- Canopy
- Fuzzy k-Means
- Streaming KMeans
- Spectral Clustering
- Clustering Commandline usage
- Options for k-Means
- Options for Canopy
- Options for Fuzzy k-Means
- Clustering Examples
- Synthetic data
- Cluster Post processing
- Cluster Dumper tool
- Cluster visualisation
- Recommendations
- First Timer FAQ
- A user-based recommender
in 5 minutes - Matrix factorization-based
recommenders - Overview
- Intro to item-based recommendations
with Hadoop - Intro to ALS recommendations
with Hadoop
Naive Bayes commandline documentation
Introduction
This quick start page describes how to run the naive bayesian and complementary naive bayesian classification algorithms on a Hadoop cluster.
Steps
Testing it on one single machine w/o cluster
In the examples directory type:
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.classifier.bayes.mapreduce.bayes.<JOB>"
-Dexec.args="<OPTIONS>"
mvn -q exec:java
-Dexec.mainClass="org.apache.mahout.classifier.bayes.mapreduce.cbayes.<JOB>"
-Dexec.args="<OPTIONS>"
Running it on the cluster
-
In $MAHOUT_HOME/, build the jar containing the job (mvn install) The job will be generated in $MAHOUT_HOME/core/target/ and it’s name will contain the Mahout version number. For example, when using Mahout 0.1 release, the job will be mahout-core-0.1.jar
-
(Optional) 1 Start up Hadoop: $HADOOP_HOME/bin/start-all.sh
-
Put the data: $HADOOP_HOME/bin/hadoop fs -put
testdata -
Run the Job: $HADOOP_HOME/bin/hadoop jar
$MAHOUT_HOME/core/target/mahout-core-
.job org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesDriver -
Get the data out of HDFS and have a look. Use bin/hadoop fs -lsr output to view all outputs.
Command line options
BayesDriver, BayesThetaNormalizerDriver, CBayesNormalizedWeightDriver, CBayesDriver, CBayesThetaDriver, CBayesThetaNormalizerDriver, BayesWeightSummerDriver, BayesFeatureDriver, BayesTfIdfDriver Usage:
[--input <input> --output <output> --help]
Options
--input (-i) input The Path for input Vectors. Must be a SequenceFile of Writable, Vector.
--output (-o) output The directory pathname for output points.
--help (-h) Print out help.