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What are the tools of data mining?
There are various tools of data mining which are as follows −
MonkeyLearn − MonkeyLearn is a machine learning platform that specializes in text mining. It is accessible in a user-friendly interface, so it can simply integrate MonkeyLearn with existing tools to implement data mining in real-time. It can begin immediately with pre-trained text mining models such as this sentiment analyzer, below, or construct a customized solution to cater to more define business requirements.
Rapid Miner − Rapid Miner is a free open-source data science platform that features thousands of algorithms for data preparation, machine learning, deep learning, text mining, and predictive analytics.
Its drag-and-drop interface and pre-built models enable non-programmers to create predictive workflows for definite use cases, like fraud detection and customer churn.
Orange Data Mining − Orange is a pure machine learning and data mining software suite. It provides the visualization and is an application-based on components written in Python computing language and advanced at the bioinformatics laboratory at the faculty of computer and information science, Ljubljana University, Slovenia.
KNIME − It is an open-source produced by KNIME.com. It is constructed by combining data mining and machine learning elements. It has been generally utilized for pharmaceutical research, business intelligence, and monetary analysis.
SSDT − SSDT stands for SQL Server Data Tools. It can expand the database development procedure in a visual studio. It is generally used for data analysis and supports solutions to solve business intelligence problems.
SSDT supports a table designer to implement table operations such as creating a table, inserting table data, deleting table data, changing table content. It enables a user to connect to the database as it supports SQL.
Rattle − Ratte is a data mining tool based on GUI. It needs the R stats programming language. Rattle exposes the statical power of R by providing essential data mining features. While rattle has a comprehensive and well-developed user interface, it has a unified log code tab that makes duplicate code for some GUI operations.
The data set developed by Rattle can be viewed and edited. Rattle provides the other facility to review the code, use it for several purposes, and extend the code without some restriction.
SAS − SAS stands for Statistical Analysis System. This tool is a good option for text mining, optimization, and data mining. It provides several methods and techniques to fulfill several analytic capabilities, which create the organization's needs and goals.
It involves descriptive modeling (helpful to categorize and profile users), predictive modeling (convenient to predict unknown outcomes), and prescriptive modeling (useful to parse, filter, and transform unstructured data including emails comment fields, books, etc.). Furthermore, its distributed memory processing architecture also creates it highly scalable.
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