Weka (weka.exe) free download, latest version 3.9.6, Weka is a collection of machine learning algorithms for solving real-world data mining problems.

Powerful Java-based data mining suite for fast machine learning, workflow automation, and visual analytics

Solve advanced data mining tasks with machine learning algorithms that can be created, tuned, and deployed automatically or manually. This tool supports data pre-processing, classification, regression, clustering, association analysis, and rich visualization for databases running on Java code, making it ideal for users seeking the best data mining software for beginners and pros alike.

Weka offers a complete set of tools to extract meaningful insights from large datasets—commonly known as data mining. Work seamlessly with filters, clusters, classifiers, regression models, associations, and more. Choose between a command-line interface for maximum performance or an intuitive GUI for simplified interaction. The Weka GUI Chooser provides quick access to its four main applications—Explorer, Experimenter, KnowledgeFlow, and SimpleCLI—plus features for capturing processed results, viewing ARFF files in spreadsheet form, running SQL worksheet queries, and working with Bayes nets. It also serves as a robust machine learning workflow automation tool and open-source data science toolkit.

Customize how your information is displayed with flexible visualization options. Plot datasets in 2D, view ROC curves, generate decision trees, explore XML BIF and DOT graphs, and visualize classifier decision boundaries. These capabilities make it a comprehensive Java-based data analysis platform built for both experimentation and production workflows.

• Complete data mining suite with classification, regression, clustering, and association tools.
• Dual interface: memory-efficient command line or user-friendly GUI.
• Access to Explorer, Experimenter, KnowledgeFlow, and SimpleCLI from one hub.
• Advanced visualization: 2D plots, ROC curves, decision trees, and structured graph formats.
• Support for ARFF viewing, SQL querying, Bayes nets, and flexible machine learning configuration.

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