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Classification of Tailor Measurements for Sowing Long Sleeve: Linear Discriminant and Quadratic Discriminant Analysis

Okoro, Joyce Adaobi, and, U.A Victor-Edema

Abstract

This work was designed to classified tailor measurements for sowing long sleeve shirt for adult individual (Male or Female) in Nigeria, using linear discriminant analysis and quadratic discriminant analysis . The multivariate data sets consisting of Seven (7) variables; Length, Shoulder length, Sleeve length, Neck, Waist length, Chest, and Round sleeve were used. Measurements of 200 adult individuals (both female and male) were randomly collected and recorded. The Linear Discriminant Analysis and Quadratic Discriminant Analysis discrimination methods were used for estimated with the help of Minitab 21 statistical software and the spreadsheet functions of Microsoft excel. The two discrimination methods were applied to classifiers tailor measurements for sowing long sleeve shirt for adult individual. The results indicate that the two discrimination methods (i.e. LDA and QDA) algorithm performs very well for this task. The resulting attained from these classifiers by implementing these two discrimination methods of tailor measurements was amazing. The study found threshold value ( h ) results for the two different discrimination methods. It was observed that linear discriminant coefficient had negative values for female individuals but for the male individuals it had positive values, therefore the threshold value (i.e. h = 0) is set as zero for classification. The quadratic discriminant function coefficient had large positive values for female individuals while the male individuals they had small positive values which tends to zero, hence the threshold value (h) is set as equal to one, (i.e. h = 1.0) for classification. Hence, the Classification Criteria for the two discrimination methods are adequate and sufficient for Classification.

Keywords

Tailor MeasurementsClassificationThreshold ValueLinear Discriminant Analysis and Quadratic Discriminant Analysis .

References

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