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HDA

Heteroscedastic Discriminant Analysis (HDA) is a machine learning algorithm for dimensionality reduction. It is implemented as a package for the open source program WEKA.

#Building Ensure you have the following programs and tools installed on your computer before proceeding.

The next step is to ensure that weka.jar is in the $CLASSPATH variable. On Arch Linux if weka was installed from the AUR, the jar is found in /usr/share/java/weka/weka.jar. To add it to the CLASSPATH on Arch add this line to your ~/.bashrc and then update your systems class path we source the bashrc.

export CLASSPATH=/usr/share/java/weka/weka.jar:$CLASSPATH
source ~/.bashrc

Next step is clone the repo,

git clone https://github.com/StephenNu/HDA.git

After that move into the location of the repo and make the package by the following commands

cd HDA
./build.bash make_package

Now in weka open the package manager and click "File/URL" under the unoffical section. Navigate to where the repo was cloned to, and go into the dist/ folder, and select HDA.zip Click okay, restart weka and HDA will be installed under filters.

#Tests Once HDA is installed, you can run the HDA tests by going to the weka command line, and running the following command

java weka.filters.HDATest

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heteroscedastic discriminant analysis (HDA) is a machine learning algorithm for dimensionality reduction. It is implemented as a package for the open source program WEKA

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