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Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques". [1]
Massive Online Analysis (MOA) is a free open-source software project specific for data stream mining with concept drift. It is written in Java and developed at the University of Waikato, New Zealand. [2]
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.
Toad Data Modeler: Quest Software: SMBs and enterprises Proprietary: Access, IBM Db2, Informix, MySQL, MariaDB, PostgreSQL, MS SQL Server, SQLite, Oracle: Windows Standalone 2005 (before this date known as CaseStudio) Tool Creator Target Business Size License Supported Database Platforms Supported OSs Standalone or bundled into a larger toolkit ...
Rattle GUI is a free and open source software (GNU GPL v2) package providing a graphical user interface (GUI) for data mining using the R statistical programming language. Rattle is used in a variety of situations.
In 2011, authors of the Weka machine learning software described the C4.5 algorithm as "a landmark decision tree program that is probably the machine learning workhorse most widely used in practice to date". [2] It became quite popular after ranking #1 in the Top 10 Algorithms in Data Mining pre-eminent paper published by Springer LNCS in 2008. [3]
A mosaic plot, Marimekko chart, Mekko chart, or sometimes percent stacked bar plot, is a graphical visualization of data from two or more qualitative variables. [1] It is the multidimensional extension of spineplots, which graphically display the same information for only one variable. [ 2 ]
Data mining is a highly effective tool in the catalog marketing industry. [citation needed] Catalogers have a rich database of history of their customer transactions for millions of customers dating back a number of years. Data mining tools can identify patterns among customers and help identify the most likely customers to respond to upcoming ...