Bhaswati Sahoo

Work place: School of Computer Engineering, KIIT Deemed University, Bhubaneswar, India



Research Interests: Computer systems and computational processes, Data Mining, Database Management System, Data Compression, Data Structures and Algorithms


Bhaswati Sahoo is Professor at the School of Computer Engineering, KIIT University, Bhubaneswar. She has good teaching and research experience. She has published numbers of Research Papers in peer-reviewed International Journals and conferences. Her areas of interest include data mining and big data. She can be reached at

Author Articles
An Optimized Model for Breast Cancer Prediction Using Frequent Itemsets Mining

By Ankita Sinha Bhaswati Sahoo Siddharth Swarup Rautaray Manjusha Pandey

DOI:, Pub. Date: 8 Sep. 2019

This presented research paper mainly studies the frequent itemsets mining approach for finding the most important attribute to overcome the existing problems in the extraction of relevant information by using data mining approaches from a huge amount of dataset. Firstly a state of art diagram for prediction is designed and data mining classifier like naive bayes, support vector machine, decision tree, k- nearest neighbour are compared and then proposed methodology with new techniques are proposed. Moreover, a new attribute filtering association frequent itemsets mining algorithm is presented. Then, by analyzing the feasibility of the proposed algorithm, the data mining classification classifier is compared. As a result, SVM produces the best result among all the classifier with attribute filtrating and without attribute filtrating. With attribute filtrating algorithm enhances the accuracy of all the other classifier.

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