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NOVEL TEXT CATEGORIZATION BY AMALGAMATION OF AUGMENTED K-NEAREST NEIGHBOURHOODCLASSIFICATION AND K-MEDOIDS CLUSTERING
2020
Zenodo
Machine learning for text classification is the underpinning of document cataloging, news filtering, document steering and exemplification. In text mining realm, effective feature selection is significant to make the learning task more accurate and competent. One of the traditional lazy text classifier k-Nearest Neighborhood (kNN) has a major pitfall in calculating the similarity between all the objects in training and testing sets, there by leads to exaggeration of both computational
doi:10.5281/zenodo.3716105
fatcat:kacxewddjfehbmm3ojtthwdtzi