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A recipe for executing Weka in Hadoop. |
Project Info
- Status: Compatible with Weka version: >= 3.7.10
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- Roadmap:
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- Future
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- work
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- -
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- distributed
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- clustering,
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- distributed
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- recommendation
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- engine,
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- pre-processing
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- for
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- text
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- mining,
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- oversampling
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- for
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- minority
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- classes
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- Availability:
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- Open
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- Source
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- -
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- -
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- manager
- Contact: mhall or use "Add Comment" at bottom of page
- JIRA: http://jira.pentaho.com/browse/DATAMINING-608
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This package for Weka >= 3.7.10
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provides
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several
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jobs
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for
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executing
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learning
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tasks
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inside
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of
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Hadoop.
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These
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include:
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- Determining
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- ARFF
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- meta
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- data
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- and
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- summary
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- statisitics
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- Computing
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- a
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- correlation
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- or
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- covariance
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- matrix
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- Training
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- a
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- Weka
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- classifier
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- or
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- regressor
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- Generating
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- randomly
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- shuffled
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- (and
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- stratified)
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- input
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- data
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- chunks
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- Evaluating
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- a
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- Weka
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- classifier
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- or
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- regressor
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- via
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- cross-validation
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- or
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- a
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- hold-out
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- set
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- Scoring
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- using
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- a
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- training
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- classifier
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- or
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- regressor
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A
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full-featured
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command
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line
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interface
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is
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available
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along
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with
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GUI
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Knowledge
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Flow
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components
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for
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job
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orchestration.
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Predictive
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models
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learned
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in
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Hadoop
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are
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fully
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compatible
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with
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Pentaho
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Data
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Integration's
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"Weka
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Scoring"
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transformation
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step.
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More information on what is available in the distributed Weka package, and how it is implemented, can be found in a three part blog posting:
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Try it out!
Open Weka's package manager (GUIChooser->Tools->Package manager) and install "distributedWekaHadoop".
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