Durai Raj Vincent P M

TL;DR: A multiclass model based on normal observations and Mahalanobis distance for agriculture development that provides 100% accuracy, recall, precision and 0% error rate when compared with other traditional classifier models is proposed.

TL;DR: A novel hybrid feature extraction procedure is explained, which is an aggregation of the correlation-based filter (CFS) and random forest recursive feature elimination (RFRFE) wrapper framework, which aims to identify an optimal subclass of features from a collection of climate, soil, and groundwater characteristics for constructing a crop-yield forecasting machine learning model with better performance and accuracy.

TL;DR: In this paper, a deep learning-based classification model with an embedded feature selection approach was used to classify Alzheimer's disease patients using an AD DNA methylation data set (64 records with 34 cases and 34 controls).

TL;DR: In this article, an ensemble decision-making model, namely VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), entropy, and standard deviation (VTOPES), is proposed for ranking the sustainable sugarcane farms.

TL;DR: Fuzzy clustering (FC) is applied to the DICOM slices to extract various clusters for different k.dimensional tissue classes, and the best-segmented image that has high inter-class rigidity is obtained using the silhouette fitness function.