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@@ -9,9 +9,10 @@ Java (convolutional or fully-connected) neural network implementation with plugi
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Go to https://github.com/amten/NeuralNetwork/releases/latest to find the latest release. Download the files NeuralNetwork.zip and BLAS-dlls.zip.
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In Weka, go to Tools/Package Manager and press the "File/URL" button. Browse to the NeuralNetwork.zip file and press "ok".
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**Important!** For optimal performance, you need to install native matrix library files.
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Windows: Unzip the BLAS-dlls.zip file to Wekas install dir (".../Program Files/Weka-3-7").
**Important!** For optimal performance on Windows, you need to copy native matrix library dll-files to Wekas install dir.
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Unzip the BLAS-dlls.zip file to Wekas install dir (".../Program Files/Weka-3-7").
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For Linux, native matrix library files have not been tested, though it should be possible to install using instructions given [here] (https://github.com/fommil/netlib-java#linux)
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### Standalone
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Include the files NeuralNetwork.jar, lib/mtj-1.0-snapshot.jar, lib/opencsv-2.3.jar in your classpath.
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**Important!** For optimal performance, you need to install native matrix library files.
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Windows: Unzip the BLAS-dlls.zip file to the directory where you execute your application, or any other directory in the PATH.
**Important!** For optimal performance on Windows, you need to copy native matrix library dll-files to the directory where you execute your application, or any other directory in the PATH.
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Unzip the BLAS-dlls.zip to that directory.
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For Linux, native matrix library files have not been tested, though it should be possible to install using instructions given [here] (https://github.com/fommil/netlib-java#linux)
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