Discriminant Functions

Network Multiple Station Discriminant Functions

Recursive Partitioning via Discriminant Functions for Rating

Aim of this paper is to propose a nonparametric method for the rating of financial stocks, such as Mutual Funds, Corporates, Equities etc. To this purpose, we refer to a procedure based on the joint use of linear discriminant analysis and tree based recursive partitioning. This method is applied when dealing with large sets of within-groups correlated covariates in order to overcome the dimensi...

A Classification Tree Based on Discriminant Functions

The classification problem is an important topic in knowledge discovery and machine learning. Traditional classification tree methods and their improvements have been discussed widely. This work proposes a new approach to construct decision trees based on discriminant functions which are learned using genetic programming. A discriminant function is a mathematical function for classifying data i...

A class of logistic-type discriminant functions

In two-group discriminant analysis, the Neyman-Pearson Lemma establishes that the ROC curve for an arbitrary linear function is everywhere below the ROC curve for the true likelihood ratio. The weighted area between these two curves can be used as a risk function for finding good discriminant functions. The weight function corresponds to the objective of the analysis, for example to minimize th...

A New Classification Approach using Discriminant Functions

There are many algorithms for, and many applications of classification and discrimination (grouping of a set of objects into subsets of similar objects where the objects in different subsets are different) in several diverse fields [2-15, 23, 24], ranging from engineering to medicine, to econometrics, etc. Some examples are automatic target recognition (ATR), fault and maintenance-time recognit...