Tools Used For Data Modeling And Predictive Analysis

2410 Words Nov 23rd, 2014 10 Pages
Weka Ashish Penti
Computer Science Department
University of North Carolina - Charlotte Charlotte, NC, U.S.A

ABSTRACT
Weka (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms developed on Java platform by University of Waikato, New Zealand. It is a data analyzing tool used for data modeling and predictive analysis. It is licensed under GNU General Public License. As it is implemented in Java it is platform independent. It is a comprehensive collection of various data preprocessing and modeling techniques. Some of the operations performed using Weka like classification, clustering etc. are discussed here. It provides implementation of various algorithms which can be applied on any kind of datasets.
It has wide range of features which perfectly suits for a data mining process. This includes preprocessing of data to clean and structure the data. Then it is followed by data classification/clustering by choosing appropriate algorithm. Weka contains four different types of interface. Each one has its own specifications. Explorer is the simple and basic interface whereas Experimenter is the most efficient of all these. Using Java Database Connectivity, it provides access to SQL databases and can be used to process the result obtained from database queries.
This article provides a brief introduction to Weka, list of few algorithms in Weka, how it is used, some of the merits and demerits of Weka and some of the future implementations that…
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