Feature selection for discrimination between low and high oil content genotypes of Indian mustard

Variable selection in discriminant analysis may be used to identify those variables which are most relevant for use in allocating future observation. It is also expected to reduce the cost of experimentation and conditional error rate by increasing the ratio of the training sample size to the dimension. Thus, feature Selection has become important task in classification and discriminant analysis.