|#The most popular tools for your data mining needs:|
There are many tools available for data mining. For only backup just look atRapid Miner (erstwhile YALE):
This is very popular since it is a ready made, open source, no-coding required software, which gives advanced analytics. Written in Java, it incorporates multifaceted data mining functions such as data preprocessing, visualization, predictive analysis, and can be easily integrated with WEKA and R-tool to directly give models from scripts written in the former two.
This is a JAVA based customization tool, which is free to use. It includes visualization and predictive analysis and modeling techniques, clustering, association, regression and classification.
This is written in C and FORTRAN, and allows the data miners to write scripts just like a programming language/platform. Hence, it is used to make statistical and analytical software for data mining. It supports graphical analysis, both linear and nonlinear modeling, classification, clustering and time-based data analysis.
Python based Orange and NTLK:
Python is very popular due to ease of use and its powerful features. There is an option available to learn moreOrange is an open source tool that is written in Python with useful data analytic s, text analysis, and machine-learning features embedded in a visual programming interface. NTLK, also composed in Python, is a powerful language processing data mining tool, which consists of data mining, machine learning, and data scraping features that can easily be built up for customized needs.
Primarily used for data preprocessing – i.e. data extraction, transformation and loading. This is also a part of data science and really help to take next step to learn more on data science. Knime is a powerful tool with GUI that shows the network of data nodes. Popular amongst financial data analysts, it has modular data pipe lining, leveraging machine learning, and data mining concepts liberally for building business intelligence reports.