AN EFFICIENCT RULE MINING MODEL USING [S]3 FCM AND ANN TECHNIQUES

ICTACT Journal on Soft Computing ( Volume: 12 , Issue: 1 )

Abstract

We are living in the era known as information era where numerous sectors especially health sectors are put to handle tremendous amount of information. To reduce this burden, an efficient data mining technology has been employed which is a successful evolving technique that has a big future for helping businesses and concentrates on the most valuable data in their data warehouses. Thus this paper presents the review of Safe Semi Supervised Fuzzy C Means clustering algorithm which is the key aspect of this work aids in achieving the goal. It has been utilized to cluster and classify the clear and relevant global data formats that many other clustering approaches unable to handle. By limiting the subsequent predictions obtained by unsupervised clustering, incorrectly labelled samples are thoroughly investigated. Meanwhile, the other labelled sample’s predictions are equivalent to the assigned labels. As a result, the labelled samples are safely examined using a combination of unsupervised clustering and SSC. Therefore, it has been clear that FCM yields better result compared to other techniques. The ANN based classification algorithm is used, which learns from the training dataset to construct a model. This model helps in the classification of new objects.

Authors

T Thamaraiselvan, K Saravanan
Prist University, India

Keywords

Data mining, Clustering, FCM, Classification, ANN

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 12 , Issue: 1 )
Date of Publication
October 2021
Pages
2504-2509

ICT Academy is an initiative of the Government of India in collaboration with the state Governments and Industries. ICT Academy is a not-for-profit society, the first of its kind pioneer venture under the Public-Private-Partnership (PPP) model

Contact Us

ICT Academy
Module No E6 -03, 6th floor Block - E
IIT Madras Research Park
Kanagam Road, Taramani,
Chennai 600 113,
Tamil Nadu, India

For Journal Subscription: journalsales@ictacademy.in

For further Queries and Assistance, write to us at: ictacademy.journal@ictacademy.in