What software to use for data mining

Data mining is the process of extracting potentially useful information and knowledge that is unknown to people in advance from a large amount of incomplete, noisy, fuzzy, and random data. The task of data mining is to discover patterns from data sets. There are many patterns that can be discovered, which can be divided into two categories according to their functions: predictive patterns and descriptive patterns.

Data mining software (Recommended learning: PHP video tutorial)

Orange

Orange is a component-based data mining and machine learning software suite. Its functions are friendly, powerful, fast and versatile visual programming front-end for browsing data analysis and visualization. , base bindings for 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 is developed in C and Python, and its graphics library is developed by the cross-platform Qt framework.

RapidMiner

RapidMiner, formerly called YALE (Yet Another Learning Environment), is a test environment for machine learning and data mining and analysis, and is also used for research real-world data mining. The experiments it provides consist of a large number of operators, which are recorded in detailed XML files and displayed by RapidMiner's graphical user interface. RapidMiner provides over 500 operators for the main machine learning processes, and it combines learning schemes with attribute evaluators for the Weka learning environment. It is a standalone tool that can be used for data analysis, and it is also 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 learning software that supports several classic data mining tasks, significantly Data preprocessing, clustering, classification, regression, virtualization, and feature selection. The technology is based on the assumption that data is presented as a single file or association, where each data point is annotated with a number of attributes. Weka uses Java's database linking capabilities to access SQL databases and process query results from a database. Its main user interface is Explorer, which also supports the same functionality as the command line, or a component-based knowledge flow interface.

JHepWork

Designed for scientists, engineers and students, jHepWork is a free open source data analysis framework that mainly uses open source libraries to create a data analysis environment , and provides a rich user interface to compete with those paid software. It is mainly designed for two-dimensional and three-dimensional graphics for scientific computing, and contains mathematical science libraries implemented in Java, random numbers, and other data mining algorithms. jHepWork is based on a high-level programming language Jython. Of course, Java code can also be used to call jHepWork's mathematics and graphics libraries.

KNIME

KNIME (Konstanz Information Miner) is a user-friendly, intelligent, and functional open source data integration, data processing, data analysis and data Exploration platform. It gives users the ability to visually create data flows or data channels, optionally run some or all analysis steps, and later explore the results, models, and interactive views. KNIME is written in Java, based on Eclipse and provides more functionality through plug-ins. Through plug-in files, users can add processing modules to files, images, and time series, and can be integrated into various other open source projects, such as: R language, Weka, Chemistry Development Kit, and LibSVM.

For more PHP related technical articles, please visit the PHP Graphic Tutorial column to learn!

The above is the detailed content of What software to use for data mining. For more information, please follow other related articles on the PHP Chinese website!