Comparison of Statistic Prediction Results in Weka Explorer Interface and Experimenter Environment Interface on Dataset

With the increased interest into data mining as an important tool for data processing and analysis, the researchers are concerned into data mining for real decision making, data mining helps in the organizational decision making, inaccurate information can mislead decisionmakers and cause costly err...

Full description

Bibliographic Details
Main Authors: Thamer Khalil, Esmeel, Roslina, Abd Hamid, Rahmah, Mokhtar
Format: Article
Language:English
Published: JETIR 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/25996/
http://umpir.ump.edu.my/id/eprint/25996/
http://umpir.ump.edu.my/id/eprint/25996/1/Comparison%20of%20Statistic%20Prediction%20Results%20in%20Weka%20Explorer%20Interface.pdf
Description
Summary:With the increased interest into data mining as an important tool for data processing and analysis, the researchers are concerned into data mining for real decision making, data mining helps in the organizational decision making, inaccurate information can mislead decisionmakers and cause costly errors. With more data collected for analytical purposes. Techniques data mining through Weka Explorer interface and experimental environment interface into determining the prediction and accuracy using different algorithm ratings to know the performance of best. Study confirm is to categorize data and help users mining useful data and easily identify an appropriate algorithm for an accurate predictive model, to access the best-performing algorithms, minimize errors and minimum time to build models through the Explorer interface and Experimental Environment Interface to get accurate.