Search Results for "c4.5 algorithm in weka"
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Showing 8 open source projects for "c4.5 algorithm in weka"
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Endpoint Protection Software for Businesses | HYPERSECUREThe HYPERSECURE endpoint protection platform is a comprehensive suite of products and services enhanced by European third-party solutions. It ensures our customers’ IT security, regulatory compliance, and digital sovereignty.
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Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK.Ditto's Edge SDK is the only thing your edge devices need to ensure your application is operational in any environment, regardless of network conditions.
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Genetic Oversampling Weka Plugin
A Weka Plugin that uses a Genetic Algorithm for Data Oversampling
Weka genetic algorithm filter plugin to generate synthetic instances. This Weka Plugin implementation uses a Genetic Algorithm to create new synthetic instances to solve the imbalanced dataset problem. See my master thesis available for download, for further details. -
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MODLEM
rule-based, WEKA compatible, Machine Learning algorithm
This project is a WEKA (Waikato Environment for Knowledge Analysis) compatible implementation of MODLEM - a Machine Learning algorithm which induces minimum set of rules. These rules can be adopted as a classifier (in terms of ML). It is a sequential covering algorithm, which was invented to cope with numeric data without discretization. Actually the nominal and numeric attributes are treated in the same way: attribute's space is being searched to find the best rule condition during rule induction. ... -
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gannu
Java API and tools for performing NLP and other AI tasks
...Gannu includes some graphical interfaces for scientific purposes. When using Gannu please cite: *Jiménez, F. V., Gelbukh, A. F. & Sidorov, G. (2013). Simple Window Selection Strategies for the Simplified Lesk Algorithm for Word Sense Disambiguation.. In F. Castro, A. F. Gelbukh & M. González (eds.), MICAI (1) (pp. 217-227), : Springer. ISBN: 978-3-642-45113-3 The zip file contains Gannu jar, source, API documentation and necessary resources for performing research. Gannu uses the following projects: Weka, JExcel API, Stanford POS Tagger and WordNet. ... -
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weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
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The most trusted software in constructionHCSS provides easy-to-use software built for construction companies that want to win more work, work smarter, and boost profits. For nearly 40 years, we've helped heavy civil contractors, infrastructure builders, and utility companies improve operations, from estimating and project management to field tracking, equipment maintenance, and safety. Tools like HeavyBid, HeavyJob, and HCSS Safety are built for the field and designed to work together, giving your team real-time visibility, tighter cost control, and better job outcomes. With 45+ accounting integrations and customizable APIs, HCSS fits seamlessly into your tech stack. We regularly update our software based on feedback from real crews, ensuring it fits the way your team works. Backed by award-winning 24/7/365 support and a proven implementation process, HCSS helps reduce risk, cut inefficiencies, and deliver fast ROI. If you're ready to grow your business and gain a competitive edge, HCSS is the partner that gets you there.
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The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for Machine Learning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
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A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
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KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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