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Most people do not understand the knowledge points of this article, "what are the free and open source web data mining tools?", so the editor summarizes the following, detailed contents, clear steps, and a certain reference value. I hope you can get something after reading this article. Let's take a look at this "free and open source web data mining tools" article.

Orange

Orange is a component-based data mining and machine learning software suite, its functions are friendly, powerful, fast and multi-functional visual programming front-end for browsing data analysis and visualization, binding Python for script development. It contains a complete set of components for data preprocessing and provides data accounting, transition, modeling, pattern evaluation and exploration functions. It was 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 an experimental environment for machine learning and data mining and analysis, and is used to study real-world data mining. The experiments it provides are composed of a large number of operators, which are recorded by detailed XML files and represented by RapidMiner graphical user interfaces. RapidMiner provides more than 500 operators for major machine learning processes and combines the learning scheme with the attribute evaluator of the Weka learning environment. It is a stand-alone tool for data analysis, as well as a data mining engine that can be integrated into your product.

Weka

Weka (Waikato Environment for Knowledge Analysis), developed by Java, is a well-known machine software that supports several classic data mining tasks, significant data preprocessing, clustering, classification, regression, virtualization, and function selection. The technique is based on the assumption that the data is in a single file or association, where each data point is labeled with many attributes. Weka uses the database linking capabilities of Java to access the SQL database and process the query results of a database. Its main user receiver is Explorer, which also supports the command line with the same function, or a component-based knowledge flow interface.

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 rich user interfaces to compete with paid software. It is mainly for two-dimensional and three-dimensional graphics for scientific computing, and includes mathematical science library realized by Java, 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 call jHepWork's math and graphics libraries.

KNIME

KNIME (Konstanz Information Miner) is a user-friendly, intelligent, and rich open source data integration, data processing, data analysis and data exploration platform. It gives users the ability to visually create data streams or data channels, selectively run some or all of the analysis steps, and follow up on the results, models, and interactive views. KNIME, written by Java, is based on Eclipse and provides more functionality through plug-ins. By using plug-in files, users can add processing modules to files, pictures, and time series, and can be integrated into a variety of other open source projects, such as R language, Weka, Chemistry Development Kit, and LibSVM.

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