Weka Gui Chooser Download LINK
Nadja Norrington
As I googled, I think it is something about classpath but I am not familiar even these things. I used weka on windows machine and I need to get used to linux systems (I am newbie on linux). So, please explain in detail.
This is an old post, but to avoid misinformation, weka can be used from the normal bash shell that most Linux distros include. It is important that you add the weka jar file to your CLASSPATH environment variable. This is done by opening the file .profile or other file in your home directory (different operating systems name this file differently). This file should already have at least a few lines with export statements. If there is already a line that says export CLASSPATH="...., then you just need to add the path to weka.jar to that list, which is :-delimited. If not, then you need to add a line, like this:
/usr/share/themes/Mist/gtk-2.0/gtkrc:48: Engine "mist" is unsupported, ignoring ---Registering Weka Editors--- java.lang.NullPointerException at weka.gui.explorer.PreprocessPanel.addPropertyChangeListener(PreprocessPanel.java:519) at javax.swing.plaf.synth.SynthPanelUI.installListeners(SynthPanelUI.java:49) at javax.swing.plaf.synth.SynthPanelUI.installUI(SynthPanelUI.java:38) at javax.swing.JComponent.setUI(JComponent.java:652) at javax.swing.JPanel.setUI(JPanel.java:131) ...This behavior happens only under Java 5/6 and Gnome/Linux, KDE doesn't produce this error. The reason for this is, that Weka tries to look more "native" and therefore sets a platform-specific Swing theme. Unfortunately, this doesn't seem to be working correctly in Java 5/6 together with Gnome. A workaround for this is to set the cross-platform Metal theme.
The following code snippet defines the dataset structure by creating its attributes and then thedataset itself. Once the weka.core.dataset.Instances object is available, rows (i.e., weka.core.dataset.Instanceobjects) can be added.
Transformations in Weka usually occur by applying filters (see section Filters below).However, quite often one only wants to quickly create a subset (of colunms or rows) from a dataset.For this purpose, the subset method of the weka.core.dataset.Instances method can be used(it uses filters under the hood to generate the actual subset):
Any class derived from OptionHandler (module weka.core.classes) allowsgetting and setting of the options via the property options. Depending onthe sub-class, you may also provide the options already when instantiating theclass. The following two examples instantiate a J48 classifier, one usingthe options property and the other using the shortcut through the constructor:
Both, GridSearch and MultiSearch, use Java Bean property names (and paths consisting of these),not command-line options in order to get/set the parameters under optimization.Using the list_property_names method of the weka.core.classes module, you can list theproperties from a Java object:
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