- #BEST MINING SOFTWARE FOR LINUX FULL#
- #BEST MINING SOFTWARE FOR LINUX SERIES#
- #BEST MINING SOFTWARE FOR LINUX FREE#
There are also fun things to try, hardware, free programming books and tutorials, and much more. There's tons of in-depth reviews, open source alternatives to proprietary software from large corporations like Google, Microsoft, Apple, Adobe, Corel, and Autodesk.
#BEST MINING SOFTWARE FOR LINUX SERIES#
The software collection forms part of our series of informative articles for Linux enthusiasts. The collection covers all categories of software. CGminer is a command line application written in C. Platforms: Windows, Mac, Linux Going strong for many years, CGminer is still one of the most popular GPU/FPGA/ASIC mining software available. Read our complete collection of recommended free and open source software. Pros: Supports GPU/FPGA/ASIC mining, Popular (frequently updated). Waikato Environment for Knowledge AnalysisĪssess evolutionary algorithms for data mining Gnome cross platform GUI for Data Mining using Rĭata mining software framework developed for use in research and teachingįull-featured data-analysis framework for scientists, engineers and students
Software environment for data stream miningĬomponent-based framework for machine learning and data miningĪimed at solving the data analysis challenges of high-energy physics Knowledge discovery in databases, machine learning, and data mining Software environment for statistical computing and graphics
#BEST MINING SOFTWARE FOR LINUX FULL#
For each application we have compiled its own portal page, providing a screenshot of the software in action, a full description with an in-depth analysis of its features, together with links to relevant resources. So, let’s explore the 11 data mining tools at hand. Hopefully, there will be something of interest here for anyone who needs to make strategic decisions when confronted with large amounts of information. This article focuses in selecting the best free software for performing data mining. Some of the common techniques include decision trees, artificial neural networks, nearest neighbour method, generic algorithms, and rule induction. There are dozens of different techniques that are used in data mining to examine and transform data. Data mining is also important in the fields of science and engineering, for surveillance, and in gaming (e.g. By embracing data mining technology, organisations can increase their revenue stream, help to minimise costs, as well as improving their competitive position. This intelligence can be used to generate accurate trends about customers’ purchasing behaviour, or to help in the assessment of customers’ credit rating. Above all, data mining is recognised as an important tool for any business as it enables data to be converted into business intelligence. This is achieved by allowing institutions to visualise and understand their data, and to identify patterns and relationships that dictate business outcomes.
It brings together the fields of computer science, statistics and artificial intelligence.ĭata mining is extremely important to the business community as it enables informed, knowledge-driven decisions to be taken. Data mining (also known as knowledge discovery) is the process of gathering large amounts of valid information, analyzing that information and condensing it into meaningful data.
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