This paper is an empirical investigation into the effectiveness of linear scaling adaptation for case-based software project effort prediction. We compare two variants of a linea...
Colin Kirsopp, Emilia Mendes, Rahul Premraj, Marti...
We present new combinatorial approximation algorithms for k-set cover. Previous approaches are based on extending the greedy algorithm by efficiently handling small sets. The new a...
Stavros Athanassopoulos, Ioannis Caragiannis, Chri...
Analysis of biopolymer sequences and structures generally adopts one of two approaches: use of detailed biophysical theoretical models of the system with experimentally-determined...
Scott C. Schmidler, Joseph E. Lucas, Terrence G. O...
We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...