Discriminant Analysis of Bronchitis Cancer Data

Khalil Dakhil, Nazera; Mahdi Al-mayali, Yahya; Dahair Al-Thabhawee, Gahssan

	Discriminant Analysis of Bronchitis Cancer Data
Journal of Kufa for Mathematics and Computer
Article 1, Volume 1, Issue 6, 2013, Pages 97-106
Authors
Nazera Khalil Dakhil; Yahya Mahdi Al-mayali; Gahssan Dahair Al-Thabhawee
Abstract
The aim of this research is to predict membership in two mutually exclusive groups of bronchitis cancer patients, and allocating new patients using Discriminant Analysis. Discrimination is a multivariate technique concerned with separating distinct sets of objects (or observations) and with allocating new objects (observation) to previously defined groups. The results showed 90% , and 98% of dead and alive patients were classified correctly. Only 2% and 10% of dead and alive patients were misclassified Introduction Discriminant analysis was first introduced by R.A. Fisher in 1936 [6]. It is rather exploratory in nature. As a separative procedure, it is often used on a onetime basis in order to investigate observed differences when fundamental relationships are not well understood. Classification procedures are less exploratory in the sense that they lead to welldefined rule, which can be used for assigning new objects. Previous studies showed the used of discriminant functions to classify three types of lesions in three groups: The normal, the benign, and the malignant. It was observed that the correctly classified carcinoma is only 42% and for normal are 100%. [7]. The main contribution of this paper is to propose a simple Fisher-type discriminant method on gene selection in microarray data.[5] Other study compared the performance of different discrimination methods for the classification of tumors based on gene expression data.[9]

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