Abstract
Abstract: Rice is one of the important cereals which feeds more than half of the world's population. It is used frequently in a variety of flavourful recipes. In this work, a dataset of Cammeo and Osmancik species found in Turkey has been selected for the study. It have 3810 samples containing seven morphological features. The feature ranking methods like Fisher score, FSV, infFS, Laplacian, ReliefF, MCFS and MUTinfFS are selected and applied on the above datasets for the purpose of finding key features for proper feature selection. After selecting key feature values, feature vector have been prepared. Then, Support vector machine technique was applied for classification based on the results obtained from feature ranking techniques.
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