I can run it on Win2k Client.
I used the following command:
C:\DJFHQ\Info_Extraction\Weka>java -classpath weka-3-2-3\weka-3-2-3\weka.jar
I have WekaMetal.jar in the CLASSPATH. I also used WinZip to "unzip" the JAR
files for Weka 3.2.3 and WekaMetal after downloading them.
My version of Java is the following:
java version "1.3.0_02"
Java(TM) 2 Runtime Environment, Standard Edition (build 1
Java HotSpot(TM) Client VM (build 1.3.0_02, mixed mode)
PS I also noticed a possible typo in your quoted string which maybe should
"G:\Program Files\Weka-3-2-3\weka.jar" i.e. the "-3" is missing.
From: Chris Bacon [mailto:firstname.lastname@example.org]
Sent: Saturday, 17 August 2002 10:29 AM
Subject: [Wekalist] WekaMetal and Windows?
Has anyone been able to run WekaMetal on Windows? I've tried on
Server from a command prompt where I get this:
G:\Program Files\WekaMetal>java -jar WekaMetal.jar:"G:\Program
Exception in thread "main" java.util.zip.ZipException: The filename,
ame, or volume label syntax is incorrect
at java.util.zip.ZipFile.open(Native Method)
at java.util.zip.ZipFile.<init>(Unknown Source)
at java.util.jar.JarFile.<init>(Unknown Source)
at java.util.jar.JarFile.<init>(Unknown Source)
I've played around with the ClassPath, but it didn't help. I've also
from within IBM Websphere Application Developer, where it gets an IO error
because it can't find the cache files (ap.cache and dc.cache), even though
they're both in the same directory as the WekaMetal.jar file.
Any help would be appreciated.
Wekalist mailing list
I am applying ID3 to a medical data set and was wondering if there is a way to
get Weka to output the results of the ID3 algorithm graphically so that the
Specialist can interpret the results easily?
I have written a classification scheme in Java using the Weka-library.
Now, I want to use the 'Experimenter' for doing some experiments
with this new classification scheme.
(Up till now I wrote my own experiments in Java, but probably the
Experimenter seems like a better option.)
In the README file it is indicated that the file
GenericObjectEditor.props is the place to be. I thus copied this
file to my home directory and I added ...
monotone.MinMaxExtension,\ #line added
monotone.OSDL #line added
This works, in the sense that in the Experimenter-gui
I now can choose from 'MinMaxExtension' and 'OSDL'.
but upon choosing one of these I get the error message
'could not create an example of weka.MinMaxExtension from the
current classpath' ...
I have to say that
1) I find it strange that the 'monotone' part is cut from the classname,
and that 'weka' is prefixed ...
2) the class 'MinMaxExtension' is part of the package 'monotone'.
I.e. the first line of 'MinMaxExtension.java' is 'package monotone;'
3) the file 'MinMaxExtension.class' is in a directory called
$SOMETHING/Source/monotone and this directory is part of my
classpath; in my .bashrc I have
Any hints on how to proceed are welcome. If possible I would like to
keep these files in the current package ....
I would like to know whether someone has written/developed an Independent Component Analysis Module For Weka.
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I would like to know the number of selected support vectors in a SVM after
a certain learning on a certain dataset. I didn't find any method to get
this information. Is it availaible ? Would it be possible to add it easily
I am facing severe performance issues. I have 4000 instances with 270 features.
I want to use the filters and wrappers to select the features. But wrappers are
taking ages to execute. So, first I applied corelated feature subset evaluation
(CfsSubsetEval) and got 97 attributes. When I applied the wrapper it is taking
more than 16 hours and still running!!! I checked wrapper with J48, KNN, and
SMO. All taking same time. I used the wrapper before but it never took that
long. I allocated 2GB memory for Java VM. What could be the reason?
I've just put a modified version of weka/core/Optimization.java into
the CVS repository. Optimization.java is used by Logistic.java
(logistic regression in Weka).
Several people have complained about the slow implementation of
logistic regression in Weka. I finally had a look at it using a
profiling tool. The old version of Optimization.java had a call to the
garbage collector (System.gc()) in one of the most frequently visited
parts of the program... Commenting that out was the main change.
(Another change was that now it doesn't create lots of Integer objects
After this change Logistic.java runs much faster (e.g. 30 times faster
on the iris data).
PS: It's a pity that this change didn't make it into the latest release
(3.4.3), but it will be in the next one. Anyway, if you are keen, you
can get the modified version from CVS.
PPS: I think there is further room for improvement in speeding up
I'm a research linguist using data mining to explore patterns in an
annotated corpus. I'm using information gain to explore correlations in
the data, but sometimes it would be useful to look at the correlation
between each value of a feature and the class attribute. Essentially if
conditional entropy H(X|Y) is:
= Σj Prob(X=vj) H(Y|X=vj)
I would like the set of Prob(X=v) H(Y|X = v) values
First of all, I apologise if this question does not make sense. I lack a
background in maths, so I'm never quite sure. But assuming it's clear,
what would be the best way to obtain a set of specific conditional entropy
statistics for each value of a given nominal feature and another
attribute? Is there a way to get this from WEKA, can you suggest another
piece of software, or would I be best off coding this myself?
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