On Classification of Data by Means of Rough Mereological Granules of Objects and Rules

Granulation of knowledge has turned an effective tool in data classification. We propose the approach to classification of data which extends our earlier methods by considering granules of either objects or decision rules obtained either from the original training set or from its granular reflection. Members of a granule vote for the decision class of that object. We present results of tests which show that this method usually gives results at least as good as the exhaustive classifier built on rough set principles.