Abstract: It has always been a challenging task to develop a fast and an efficient incremental linear discriminant analysis (ILDA) algorithm. For this purpose, we conduct a new study for linear ...

ABSTRACT: This work describes a data integration model using the Statistical Matching methodology (hot deck distance) to integrate two surveys conducted by ISTAT (EU-SILC) and the Bank of Italy ...

Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States Navigating the complex landscape of single-cell transcriptomic data presents significant ...

Abstract: Discriminant analysis is a technique used in statistics and machine learning to separate two or more classes of objects or events. We introduce linear, quadratic, and mixture discriminant ...

Autism Spectrum Disorder (ASD) is a developmental condition characterized by social and communication differences. Recent research suggests ASD affects 1-in-44 children in the United States. ASD is ...

Sourabh has worked as a full-time data scientist for an ISP organisation, experienced in analysing patterns and their implementation in product development. He has a keen interest in developing ...

FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in ...

Dimensionality reduction is the transformation of data from high dimensional space into a low dimensional space so that low dimensional space representation retains nearly all the information ideally ...