Dutta S

Manideep B.C.S

Basha S.M

Caytiles R.D

Iyengar N.C.S.N.

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

International Journal of Grid and Distributed Computing

In Machine Learning and statistics attribute/feature selection is used in predictive model construction. This help the Machine in interpreting the features easily by discovering good insight and improves efficiency in predictive modeling. The objective of our research is to improve the classification accuracy by knowing the most important feature from any given dataset. In this research, we used two techniques namely Data partition and K Fold, in evaluating the importance of each feature from the randomly generated dataset with 5399 instances and 20 attributes. In Data partitioning, the attribute with lowest accuracy is filtered out. Where as in K Fold cross validation, attributes with biggest error is removed from the original dataset. In our experiments, the evaluation parameters considered are Recall. Precision and F-Measure. Finally the accuracy rate of both the techniques are compared. The finding in our research stats that K Fold approach achieves better accuracy of 97.03% than Data partitioning(96.11%) in estimating the importance of features in classification. © 2018 IEEE.

2018 8th International Conference on Communication Systems and Network Technologies (CSNT)

Evaluating the Importance of each Feature in Classification task

International Journal of Security and Its Applications

Analyzing the performance of Various Fraud Detection Techniques

Physics Today

Preprint repository arXiv achieves milestone million uploads

IEEE Transactions on Medical Imaging

Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy

2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

Role of Image Contrast Enhancement Technique for Ophthalmologist as Diagnostic Tool for Diabetic Retinopathy

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)

Discriminant color texture descriptors for diabetic retinopathy recognition

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

An efficient method of detecting exudates in diabetic retinopathy: Using texture edge features

Classification of Diabetic Retinopathy Images by Using Deep Learning Models

Journal	International Journal of Grid and Distributed Computing
Publisher	NADIA
ISSN	2005-4262
Open Access	Yes