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1.0.1 No LVQ: Cluster data using the Learning Vector Quantization algorithm.
#WEKA JAR WITH SPEGASOS DRIVER#
1.0.0 No JDBCDriversDummyPackage: Dummy package that provides a place to drop JDBC driver jar files so that they get loaded by the system. 1.0.3 No J48graft: Class for generating a grafted (pruned or unpruned) C4.5 decision tree 3.0 No J48Consolidated: Class for generating a pruned or unpruned C45 consolidated tree
![weka jar with spegasos weka jar with spegasos](https://www.softwaretestinghelp.com/wp-content/qa/uploads/2020/07/WEKA-tutorial-2.png)
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1.0.0 No IWSSembeddedNB: Incremental Wrapper Subset Selection with embedded NB classifier 1.0.0 No IWSS: Incremental Wrapper Subset Selection 1.0.1 No IBkLG: Log and Gaussian kernel for K-NN 1.0.0 No GPAttributeGeneration: Genetic Programming Attribute Generation 1.0.0 No EvolutionarySearch: An Evolutionary Algorithm (EA) to explore the space of attributes. 1.0.1 No EMImputation: Replaces missing numeric values using Expectation Maximization with a multivariate normal model. 1.0 No EAR4: Case-Based Regression Learner 1.0.0 No DistributionBasedBalance: Distribution-based balancing of datasets 1.0.1 No DilcaDistance: Learning distance measure for categorical data 1.0.3 No DTNB: Class for building and using a decision table/naive Bayes hybrid classifier. 1.0.1 No DMNBtext: Class for building and using a Discriminative Multinomial Naive Bayes classifier 1.0.0 No CVAttributeEval: An Variation degree Algorithm to explore the space of attributes. 1.0.1 No CLOPE: CLOPE: a fast and effective clustering algorithm for transactional data 1.0.1 No CHIRP: CHIRP: A new classifier based on Composite Hypercubes on Iterated Random Projections 1.0 No CAAR: Context Aware Case-Based Regression Learner 1.0.0 No ArabicStemmers_LightStemmers: Arabic Stemmer / Light Stemmer 1.2.1 No AnDE: Averaged N-Dependence Estimators (includes A1DE and A2DE)