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Today, I would like to introduce to you what big data mining tools and software have. The content of the article is good. Now I would like to share it with you. Friends who feel in need can understand it. I hope it will be helpful to you. Let's read it along with the editor's ideas.

For data mining, because of the important position of data mining in big data industry, the software tools used put more emphasis on machine learning, and the commonly used software tool is SPSS Modeler. SPSS Modeler mainly provides machine learning algorithms for commercial mining. at the same time, it is also very convenient in data preprocessing and result assistant analysis, which is especially suitable for fast mining in commercial environment, but its processing capacity is not very strong. Once faced with too large data scale, it is very difficult to use. Therefore, the following editor will introduce some other big data software tools.

1 、 Rapid Miner

Rapid Miner is a data science software platform that provides an integrated environment for data preparation, machine learning, deep learning, text mining and predictive analysis. It is one of the leading open source systems for data mining. The program is written entirely in Java programming language. The program provides an option for users to try out a large number of arbitrarily nested operators, which are detailed in the XML file and can be built by Rapid Miner's graphical user interface.

2 、 Orange

Orange is an open source toolkit for data visualization, machine learning and data mining. It has a visual programming front end that can be used for exploratory data analysis and interactive data visualization. Orange is a component-based visual programming package for data visualization, machine learning, data mining and data analysis. Orange components, called window components, range from simple data visualization, subset selection and preprocessing to evaluation of learning algorithms and predictive modeling. Visual programming of Orange is done through the interface, where workflows are created by connecting predefined or user-designed window components, while advanced users can use Orange as a Python library to manipulate data and change window components.

3 、 Kaggle

Kaggle is the world's community of data scientists and machine learners. Kaggle started as a machine learning competition, but now it has gradually become a public cloud-based data science platform. Kaggle is a platform that helps solve problems, recruit strong teams, and promote the power of data science.

4 、 Weka

Waikato knowledge Analysis Environment (Weka) is a set of machine learning software developed by the University of Waikato in New Zealand. The software is written in Java. It contains a series of visualization tools and algorithms for data analysis and predictive modeling, with a graphical user interface. Weka supports several standard data mining tasks, more specifically, data preprocessing, clustering, classification, regression, visualization and feature selection.

5 、 R-Programming

R language is widely used in data mining, statistical software development and data analysis. Do you think the famous R only has data-related functions? In fact, it also provides statistical and mapping techniques, including linear and nonlinear modeling, classical statistical testing, time series analysis, classification, collection, and so on.

The abbreviation of R, R, As a free software for statistical calculation and mapping for programming language and software environment, it is mainly written in C language and FORTRAN language, and many modules are written by R, which is a great feature of R. Moreover, because of its excellent ease of use and scalability, R has greatly improved its popularity in recent years, and it has gradually become one of the commonly used tools for data people.

6 、 NLTK

NLTK, a famous open source data mining tool, provides a language processing tool, including data mining, machine learning, data capture, emotion analysis and other language processing tasks. Therefore, it has been in an invincible position in the field of language processing tasks. Users who want to feel this popular tool for data people can continue their N-day tour by installing NLTK and dragging a package to their favorite task, and its high intelligence is one of the biggest reasons why the tool is so popular. In addition, it is written in Python language, users can directly build applications on it, but also can customize small tasks, very convenient.

These are all the contents of big data mining tools software, and more related to big data mining tools software can search the previous articles or browse the following articles to learn ha! I believe the editor will add more knowledge to you. I hope you can support it!

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