AIMC Topic: Discriminant Analysis

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PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.

Journal of molecular modeling
The prediction of domain/linker residues in protein sequences is a crucial task in the functional classification of proteins, homology-based protein structure prediction, and high-throughput structural genomics. In this work, a novel consensus-based ...

Machine Learning Biogeographic Processes from Biotic Patterns: A New Trait-Dependent Dispersal and Diversification Model with Model Choice By Simulation-Trained Discriminant Analysis.

Systematic biology
Current statistical biogeographical analysis methods are limited in the ways ecology can be related to the processes of diversification and geographical range evolution, requiring conflation of geography and ecology, and/or assuming ecologies that ar...

Automated identification of copepods using digital image processing and artificial neural network.

BMC bioinformatics
BACKGROUND: Copepods are planktonic organisms that play a major role in the marine food chain. Studying the community structure and abundance of copepods in relation to the environment is essential to evaluate their contribution to mangrove trophodyn...

Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition.

IEEE transactions on cybernetics
Robust descriptor-based subspace learning with complex data is an active topic in pattern analysis and machine intelligence. A few researches concentrate the optimal design on feature representation and metric learning. However, traditionally used fe...

Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

PloS one
This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a ...

An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images.

Scientific reports
This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster sca...

Artificial Neural Network applied as a methodology of mosquito species identification.

Acta tropica
There are about 200 species of mosquitoes (Culicidae) known to be vectors of pathogens that cause diseases in humans. Correct identification of mosquito species is an essential step in the development of effective control strategies for these disease...

Superiority of artificial neural networks for a genetic classification procedure.

Genetics and molecular research : GMR
The correct classification of individuals is extremely important for the preservation of genetic variability and for maximization of yield in breeding programs using phenotypic traits and genetic markers. The Fisher and Anderson discriminant function...

Optimal combination of feature selection and classification via local hyperplane based learning strategy.

BMC bioinformatics
BACKGROUND: Classifying cancers by gene selection is among the most important and challenging procedures in biomedicine. A major challenge is to design an effective method that eliminates irrelevant, redundant, or noisy genes from the classification,...