Reducing rule generation complexity in the prism algorithm

Other Title(s)

تقليل وقت عملية توليد القواعد في خوارزمية برزم

Dissertant

Hammadi, Muhammad Yasin

Thesis advisor

al-Zubaydi, Rashid A.

Comitee Members

Duwayri, Rehab
al-Ghul, Said
Alawinah, Ali
al-Emam, Nimr

University

Philadelphia University

Faculty

Faculty of Information Technology

Department

Department of Computer Science

University Country

Jordan

Degree

Master

Degree Date

2014

English Abstract

-Data mining is a computer science field that works on finding the relations and patterns that are found within data (training data), by detecting these relations and patterns, rules can be created, that can be used later on to filter out and process future data (test data).

Prism is an easy covering algorithm depending on separate-and-conquer algorithms; this algorithm creates rules by discovering the power of relations between attribute items with the objective class.

The primary phase in Prism is the rule creation phase, where the relation power between every attribute item and the targeted class is computed in every assumption, then the set of training data is classified based on the output results.

One of the primary pillars in the rule generation step is that whenever Prism detects two equal strength values, Prism selects one value only and drops the other to the next iteration of computations and filtering.

However, observations and experiments over more than one data set proved that in each time the other equal value is always chosen in the next iteration, this is obviously unneeded system overhead.

In this thesis, we aim to remove this redundancy in rule generation phase by presenting the enhanced prism (E-Prism) algorithm.

Another insufficiency in this algorithm is that it deals with only categorical attributes, some discretization methods where previously used with Prism, but the problem with these techniques is their large calculation complexity compared to other discretization methods.

This thesis aims overcome this problem by using discretization methods with small complexity as a pre-processing phase allowing Prism to deal with continuous attributes.

Main Subjects

Mathematics

Topics

• Algorithms
• Data mining

No. of Pages

50

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-546248