Questions tagged [weka]

Weka (Waikato Environment for Knowledge Analysis) is an open source machine learning library written in Java.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Weka is open source software issued under the GNU General Public License.

Weka's main user interface is the Explorer, but essentially the same functionality can be accessed through the component-based Knowledge Flow interface and from the command line. There is also the Experimenter, which allows the systematic comparison of the predictive performance of Weka's machine learning algorithms on a collection of datasets.

The Explorer interface features several panels providing access to the main components of the workbench:

  • The Preprocess panel has facilities for importing data from a database, a CSV file, etc., and for preprocessing this data using a so-called filtering algorithm. These filters can be used to transform the data (e.g., turning numeric attributes into discrete ones) and make it possible to delete instances and attributes according to specific criteria.
  • The Classify panel enables the user to apply classification and regression algorithms (indiscriminately called classifiers in Weka) to the resulting dataset, to estimate the accuracy of the resulting predictive model, and to visualize erroneous predictions, ROC curves, etc., or the model itself (if the model is amenable to visualization like, e.g., a decision tree).
  • The Associate panel provides access to association rule learners that attempt to identify all important interrelationships between attributes in the data.
  • The Cluster panel gives access to the clustering techniques in Weka, e.g., the simple k-means algorithm. There is also an implementation of the expectation maximization algorithm for learning a mixture of normal distributions.
  • The Select attributes panel provides algorithms for identifying the most predictive attributes in a dataset.
  • The Visualize panel shows a scatter plot matrix, where individual scatter plots can be selected and enlarged, and analyzed further using various selection operators.

Online Resources:

Use Weka in your Java Code

Weka on Sourceforge

Weka on GitHub

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Weka: How do I get the prediction value in java for a test instance?

I have successfully trained a classifier (bayesnet) and constructed a test set (ARFF-format), which has one instance, with one missing value. Evaluation eTest = new Evaluation(trainingInstance); eTest.evaluateModel(bayes_Classifier,…
M.R.
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Regarding the approach of displaying a classification/decision tree from the command line?

In Weka, how to display a classification/decision tree from the command line?
user288609
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What platform / tool / software / language should i use for text mining?

I am a begineer to the field of text mining . I need to perform work on the document similarity .I aim at comparing two documents and then providing the similarity between them in terms of a number. I have read a lot of theory about this . I am…
siddharth
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Find best available data in a given data set according to input data using WEKA?

I tried to use a clear title. What I try to achieve is that I have a list of data as below ID - ID of people, not important in calculation, but need for output to determine the person Education {1=Degree, 2=Master, 3=PhD} CGPA - value from 2.00…
OmerHalit
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WEKA: usage of crossValidateModel

I was trying to follow the weka example using Eclipse, which is about decision tree evaluation and copied from weka page http://weka.wikispaces.com/Generating+classifier+evaluation+output+manually Classifier cls = new J48(); Evaluation eval = new…
user1109094
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Does a filter need to be applied before running cross validation in WEKA

I want to run n fold cross validation on some classifiers I am using. I found example code on the WEKA Wiki (here is the WekaDemo.java) but this applies a filter before running the validation. Does this always need to be done or is this not…
Chris
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Optimizing SMO with RBFKernel (C and gamma) in Weka

I'm trying to train a set of ~30,000 instances using an SMO classifier with an RBFKernel in Weka. I'm using grid search to find the optimal values for the parameters C and gamma. Here is my configuration: weka.classifiers.meta.GridSearch -E ACC…
melhosseiny
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Getting weka to cross-validate a classifier from Ruby

Taking a hint from here! I'm utilising weka's library of classifiers from Ruby via RJB. I want to be able to create a classifier from an .arff file and run 10 fold cross-validation with it to produce a confusion matrix as explained in the Weka…
Nat
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How can I use SVM in Java

I'm extremally new to SVM. I need to extract sentences from text and I have found an article that explains how to do it by using SVM algorithm. How can I implement SVM in Java? Is it correct to use Weka to solve my problem?
fedor.belov
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How to convert the nominal data from csv to arff format?

one of the attribute was 'first year, second year'. when i tried to open into Weka, i got the errors the following error message "unable to determine structure as arff(Reasons:java.lang.IllegalArgumentException: A nominal attribute (year) cannot…
Ridji
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Weka API : 'Multiplication is only applicable to doubles!' during buildForecaster

I'm facing an error when using Weka API in spring boot that says 'Multiplication is only applicable to doubles!' while working with the Weka library. The error occurs during the execution of this code …
trey
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Error in Weka's Gaussian Processes algorithm: Multiplication is only applicable to doubles

I have this dataset I want to apply weka algorithm to it by request an API @RELATION dataset @ATTRIBUTE timestamp DATE "yyyy-MM-dd HH:mm:ss z" @ATTRIBUTE action {scale_up} @ATTRIBUTE duration NUMERIC @ATTRIBUTE useful {0,1} @DATA "2023-07-05…
trey
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calling WEKA Ridor classifier from MATLAB

I can call J48 from MATLAB with no problem. But when I try the same with Ridor I'm getting fault code classifier = weka.classifiers.trees.J48(); object classifier is created c=weka.classifiers.rules.Ridor(); ??? Undefined variable "weka"…
Krzysztof Fajst
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Weka unable to read arff file

everyone.. I try to open an arff file using weka but the error appear as below: java.io.IOException: Unable to determine structure as arff (Reason: java.io.IOException: } expected at end of enumeration, read Token[EOL], line 6) This is part of the…
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How to use the derived models by WEKA to apply for new input data

I am using WEKA 3.8.6 to generate models for prediction purposes. I have the model but I do not know how to use my own parameters to see the results by utilizing the model. What may I do? I am trying to develop and compare the set of models for…
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