DETECTION OF FREQUENT ITEMS FROM THE DATASET USING UNSTRUCTURED DATA CLASSIFICATION

Abstract
In this article, association classification algorithms are utilised as a novel technique adopted lately by certain researchers in text categorization. Our tests using five distinct class newspapers gathered from various news sources are capable of performing well and provide higher exactness compared to the KNN, NB, and SVM. As a future study, we suggest the implementation of similar algorithms based on association rules and comparisons with ours. In addition, researchers in this field might be interested in studying the multi-labeling feature of our classification method.

Authors
M Keerthana
Paavai Engineering College, India

Keywords
Association classification, frequent itemset, unstructured classification, SVM
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 2 , Issue: 3 )
Date of Publication :
June 2021

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