Erimafa, Iduseri, and Edokpa, (2009) carried out a study to predict the class of degree obtained in university system by using discriminant
In this paper, we propose a semi-supervised multi-view manifold discriminant
intact space learning (S[M.sup.2]DIS) approach.
Before implementing the canonical discriminant
analysis, Pearson's correlation among the variables was conducted to identify the variables which were not important for study.
One of them is Generalized Singular Value Decomposition (GSVD)  which is generally applied by various discriminant
analysis approaches [18, 19].
analysis using MANOVA is done to factor out the variables that differentiate investors on the basis of age, income-group and the type of investors.
Although we extracted five discriminant
functions, only the first one proved significant at the level of p<0.05.
The sources said the project is, therefore, aimed to identify discriminant
sub-bands for efficient and robust face recognition.
These body parameters are also better assessed using multivariate principal component and discriminant
analyses than the univariate approach (Yakubu et al., 2009; Malomane et al., 2014; Ribeiro et al., 2016; Dahloum et al., 2016).
Numerous scholars have carried out considerable research on water inrush source models and obtained great success in their practical application, However, present discriminant
methods have not considered the complicated information superposition problem between hydrochemical data, a problem that results in misdiscrimination of the established model in the practical application process, and their discrimination accuracy still needs further improvement.
functions are especially effective in the case of gulls (Laridae), allowing correct sexing from 90 to 100 % of individuals from different species (Mawhinney & Diamond 1999, Chochi et al.
analysis is a multivariate statistical method that can distinguish newly acquired samples according to the quantitative characteristics of the existing observational sample.
The purpose of this paper is to design and develop a credit risk rating model for Indian state-owned banks based on multivariate discriminant
analysis (MDA) using both financial and non-financial variables and find which category of variables had the strongest impact within the given samples.