Machine learning and data mining software Rollup

Source: Internet
Author: User
Tags rapidminer
Summary:Orange Orange is a component-based data mining and machine learning software suite that features a friendly, yet powerful, fast and versatile visual programming front end for browsing data analysis and visualization, and the base binds Python for scripting development. It packs


Orange is a component-based data mining and machine learning software suite that features a friendly, yet powerful, fast and versatile visual programming front end for browsing data analysis and visualization, binding Python for scripting development. It contains a complete set of components for data preprocessing and provides the functions of data Accounting, transition, modeling, model evaluation and exploration. It is developed by C + + and Python, and its graphics library is developed by a cross-platform QT framework. RapidMiner

RapidMiner, formerly known as Yale (yet another learning environment), is a test environment for machine learning and data mining and analysis, and is used to study real-world data mining. It provides experiments consisting of a large number of operators, which are recorded by detailed XML files and displayed by RapidMiner graphical user interfaces. RapidMiner provides more than 500 operators for the main machine learning process, and combines a learning program with a property evaluator for the Weka learning environment. It is a standalone tool that can be used for data analysis as well as a data mining engine that can be used to integrate into your product. Weka

The Java-developed Weka (Waikato Environment for knowledge analysis) is a well-known machine software that supports several classic data mining tasks, significant data preprocessing, clustering, classification, regression, virtualization, and feature selection. Its technology is based on hypothetical data that is in a single file or associated, where each data point is labeled by many attributes. Weka uses the Java database link capability to access the SQL database and can process the results of a database query. Its main user interface is the Explorer, which also supports the same function command line, or a component-based knowledge flow interfaces. jhepwork

Designed for scientists, engineers, and students, jHepWork is a free open source data analysis framework that uses open source libraries to create a data analysis environment and provides a rich user interface to compete with those charged software. It is mainly for the scientific calculation of the two-and three-dimensional mapping, and contains the implementation of Java-based mathematical science library, random numbers, and other data mining algorithms. jHepWork is based on a high-level programming language Jython, and of course Java code can also be used to invoke jHepWork's math and graphics libraries. Knime

Knime (Konstanz information Miner) is a user-friendly, intelligent, and abundant open source data integration, data processing, analysis and data exploration platform. It gives the user the ability to visually create a data stream or data channel, optionally running some or all of the analysis steps, with later research results, models, and an interactive view. Knime is written in Java and provides more functionality based on Eclipse and plug-ins. With plug-in files, users can add processing modules to files, images, and time series, and can be integrated into a variety of other open source projects, such as the R language, Weka,chemistry development Kit, and LIBSVM.


C4.5,weka, Xelopes is a three free software

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