A brief explanation of all software used in data mining.

1. Softwares used in Data Mining
Ujjwal Jain (14BIE009)
Ronak Tiwari (14BIE038)
Vishruth Kumar (14BIE042)

2. Data Mining
 Set of methodologies used in analyzing data from various
dimensions and perspectives
Descriptive
Power Predictive
Power

3. Data mining techniques
Techniques
Regression
Associate
rule
Classification
Clustering

4. Softwares
Rapid miner
Weka
Orange
R Programming

5. Rapid Miner
 Ready made, open source, no-coding required software
 Written in Java, it incorporates multifaceted data mining
functions such as data pre-processing, visualization,
predictive analysis, and can be easily integrated with
WEKA and R-tool to directly give models from scripts
written in the former two.
 The software also features built-in templates, repeatable
work flows, a professional visualization environment, and
seamless integration with languages like Python and R into
work flows that aid in rapid prototyping.

6. Weka
 Weka is a collection of machine learning algorithms for
data mining tasks.
 The algorithms can either be applied directly to a dataset
or called from your own Java code.
 Weka contains tools for data pre-processing,
classification, regression, clustering, association rules,
and visualization.
 It is also well-suited for developing new machine learning
schemes.