Artificial Intelligence

    

Table based KNN Variants for Categorizing Words

Authors: Taeho Jo

In this research, we propose the table based KNN variants, as the approach to the word categorization. The initial KNN version which receives a table as its input data was previously proposed as the tool of such task. In this research, we mention the three KNN variants: one where the selected nearest neighbors are discriminated by their similarities with a novice example, one where the attributes are discriminated by their correlations with the target outputs, and one where the training examples are discriminated by their credits. In this research, we modify the three KNN variants as well as the initial version of the KNN algorithm. As the goal of this research, we try to improve the classification performance bymodifying the KNN variants so.

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[v1] 2026-01-13 21:20:39

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