scholarly journals Discrimination and Classification of Poultry Feeds Data

2013 ◽  
Vol 2 (5) ◽  
pp. 37-44
Author(s):  
Olosunde A.A ◽  
Soyinka A.T
Keyword(s):  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Discriminant Function ◽  
Copper Salt ◽  
Analysis Method ◽  
Linear Discriminant ◽  
Discriminant Analysis Method ◽  
Organic Copper ◽  
Fisher’S Linear Discriminant

This study is aimed at employing discriminant analysis method and classification for the purpose of achieving the assessment of a discriminant function through which we can discover the reasons of the actual difference between two groups of eggs of which the chicken were fed with different combination of feeds. Fisher’s Linear Discriminant Function (LDA) was used as a tool for the Statistical analysis. It was estimated on the basis of a sample of 96 chickens, which were classified into two groups of 48 chickens each. One group was fed with in-organic copper salt combination while the second group with organic copper salt combination. Some important attributes are measured from the eggs produced from these two groups; such as egg’s size(g) and cholesterol level(mg).The results obtained assert the efficiency of the discriminant function which we obtained and the possibility of its use for the purpose of discriminating and classifying the eggs of unknown feeds into corresponding group in future.

scholarly journals Identification of Wheat Varieties with a Parallel-Plate Capacitance Sensor Using Fisher’s Linear Discriminant Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
C. V. K. Kandala ◽  
K. N. Govindarajan ◽  
N. Puppala ◽  
V. Settaluri ◽  
R. S. Reddy
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Parallel Plate ◽  
Wheat Variety ◽  
Capacitance Sensor ◽  
Wheat Varieties ◽  
Linear Discriminant ◽  
Variety Classification ◽  
Fisher’S Linear Discriminant

Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models.Zandθof a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and theCvalue was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry.

An Improved Linear Discriminant Analysis Method and its Application to Face Recognition

2014 ◽  
Vol 556-562 ◽  
pp. 4825-4829 ◽  
Author(s):  
Kai Li ◽  
Peng Tang
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Extraction Method ◽  
Analysis Method ◽  
Scatter Matrix ◽  
Linear Discriminant ◽  
Feature Extraction Method ◽  
Discriminant Analysis Method

Linear discriminant analysis (LDA) is an important feature extraction method. This paper proposes an improved linear discriminant analysis method, which redefines the within-class scatter matrix and introduces the normalized parameter to control the bias and variance of eigenvalues. In addition, it makes the between-class scatter matrix to weight and avoids the overlapping of neighboring class samples. Some experiments for the improved algorithm presented by us are performed on the ORL, FERET and YALE face databases, and it is compared with other commonly used methods. Experimental results show that the proposed algorithm is the effective.

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