6 very good open source data mining tools recommended

1, RapidMiner

The tool is written in the Java language and provides advanced analysis techniques through a template-based framework. The biggest benefit of this tool is that users don't have to write any code. It is provided as a service rather than as a local software. It is worth mentioning that the tool topped the list of data mining tools.

In addition to data mining, RapidMiner provides features such as data preprocessing and visualization, predictive analytics, and statistical modelling, evaluation, and deployment. What's more, it also provides learning scenarios, models, and algorithms from Weka (an intelligent analysis environment) and R scripts.

RapidMiner is distributed under AGPL Open Source license and can be downloaded from sourceforge. SourceForge is a centralized place for developers to manage a wide range of open-source projects, including the mediawiki used by Wikipedia.

2, WEKA

Weka's native non-Java version was developed primarily to analyze data in the agricultural sector. Based on the Java version, the tool is very complex and is used in many different applications, including data analysis and predictive modeling visualization and algorithms. The advantage over RapidMiner is that it is free under the GNU General Public License, because users can choose to customize according to their preferences.

Weka supports a variety of standard data mining tasks, including data preprocessing, collection, classification, regression analysis, visualization, and feature selection.

After adding a sequence model, the Weka will become more powerful, but not currently included.

3, R-programming

What would you think if I told you that the R project, a GNU project, was written by R (R-programming, hereinafter referred to as R) itself? It is mainly written in C and Fortran, and many modules are written by R, This is a free software for statistical calculation and mapping of programming languages and software environments. The R language is widely used in data mining, as well as in the development of statistical software and data analysis. In recent years, ease of use and scalability have greatly increased the visibility of R.

In addition to data, it provides statistical and cartographic techniques, including linear and nonlinear modeling, classical statistical testing, time series analysis, classification, collection, and so on.

4. Orange

Python is popular because it is easy to learn and powerful. If you're a python developer, there's nothing more appropriate than orange when it comes to finding a tool to work with. It is a python-based, powerful open source tool that works for both beginners and expert-level gods.

In addition, you will definitely fall in love with visual programming and Python scripting for this tool. It has not only machine learning components, but also biological information and text mining, can be said to be full of data analysis of various functions.

5, Knime

There are three main parts of data processing: extraction, conversion and loading. And all three knime can do it. Knime provides you with a graphical user interface for processing data nodes. It is an open source data analysis, reporting, and synthesis platform that integrates machine learning components and data mining through the pipelining concept of its modular data, and raises the focus of business intelligence and financial data analysis.

Knime is based on Eclipse, written in Java, and easy to extend and supplement plugins. Its additional functionality can be added at any time, and its large number of data integration modules are included in the core version.

6, NLTK

When it comes to language processing tasks, nothing beats nltk. NLTK provides a language processing tool that includes data mining, machine learning, data capture, sentiment analysis, and many other language processing tasks. All you need to do is install NLTK and drag a package to your favorite task so you can do something else. Because it's written in the Python language, you can build the app on it and customize its small tasks.

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Recommended 6 Very good open source data mining tools