Examples (command line)¶
To run MOA with MOAFS
from command line, you can use the following commands. /home/athos/Documentos/datasets/usenet1.arff
is the directory in your computer where the data set is located.
Parameters¶
MOAFS
uses a set of different parameters. They are:
-f
: Reduction rate - The number of features to select (default = 10)-w
: Processing window - The number of instances to process using the specified reduction rate (default = 1)-m
: Feature Selection Method - Feature selection method to be used. Options: 0. No method. 1. Information Gain 2. Symmetrical Uncertainty 3. Chi-Squared 4. Cramers V-Test 5. Gain Ratio 6. Extremal Feature Selection 7. Online Feature Selection
Classification without feature selection (No method)¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Information Gain¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 1) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 1) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Symmetrical Uncertainty¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 2) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 2) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Chi-Squared¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 3) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 3) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Cramers V-Test¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 4) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 4) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Gain Ratio¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 5) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 5) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Extremal Feature Selection¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 6) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 6) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Online Feature Selection¶
LINUX/MAC
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 7) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
WINDOWS
java -cp .;moafs.jar;moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 40 -m 7) -s (ArffFileStream -f C:\Users\athos\Download\usenet1.arff) -f 100"
Changes in Reduction rate¶
Simply change the value for the -f
parameter in your command line. If you do not want to perform any reduction, just omit it. For instance:
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
If you want a particular number, e.g. 4000 attributes, add it after the -f
parameter:
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 4000 -m 6) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
Changes in Processing window¶
Simply change the value for the -w
parameter in your command line. If you do not want to specify a processing window, just omit it and the default (1) will be used. For instance:
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
If you want a particular number, e.g. 1000 instances, add it after the -w
parameter:
java -cp moafs.jar:moa.jar -javaagent:sizeofag-1.0.4.jar moa.DoTask "EvaluateInterleavedTestThenTrain -l (moa.featureselection.classifiers.NaiveBayes -f 4000 -m 6 -w 1000) -s (ArffFileStream -f /home/athos/Documentos/datasets/usenet1.arff) -f 100"
For further documentation on MOA, please refer to https://moa.cms.waikato.ac.nz/documentation/.