A Discrete Formulation of Unified Data Mining Model | [Nucleus • 2020]

Author(s):

1. D.M. Khan: Department of Computer Science and IT, The Islamia University of Bahawalpur, Pakistan

2. A.U. Rehman: Department of Information Technology,KFUEIT, Rahim Yar Khan, Pakistan

3. M.U. Rehman: Department of Computer Science, KFUEIT, Rahim Yar Khan, Pakistan

4. F. Shahzad: Department of Computer Science and IT, The Islamia University of Bahawalpur, Pakistan

5. N. Saher: Department of Computer Science and IT, The Islamia University of Bahawalpur, Pakistan

Abstract:

A race is going on to process the complex and huge amount of data. To achieve this, data analytics are proposing different models and methods. Parallel to this, rich research work has been done to simplify different mathematical models for the validation and for the acceptance level of calculated knowledge. In this paper, we propose a discrete formulation of a unified data mining model. It envisages that knowledge extraction is a multi-step process where different data mining processes such as clustering, classification and visualization are unified in a cascade way; that is, an output of a process is the input to another process which helps to achieve scalability and flexibility on a larger scale. Simultaneously, to prove whether our proposed model is valid or invalid, it is evaluated by discrete structure. For this, different mathematical formulations are formed to support the cause and then these mathematical formulations are evaluated to achieve the required target. Each mathematical formulation is examined in detail by using a simple technique called Truth Table and its Truth Values. Truth Table shows that evaluated mathematical formulations are valid and correct.

Page(s): 135-140

DOI: DOI not available

Published: Journal: Nucleus, Volume: 57, Issue: 4, Year: 2020

Keywords:

Unified Data Mining Theory UDMT , Unified Data Mining Framework UDMF , Unified Mining Theory UMT , Unified Theory UT , Unified Data Mining UDM

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