Genetic Algorithm Based Term Selection for Nursing-Care Freestyle Japanese Text Classification

Abstract

In this paper, we propose two term selection methods for classifying nursing-care texts. In a term selection method based on GA, two objectives which are maximizing correctly classified texts and minimizing selected terms are optimized. The weighted sum of these two objectives was used as the evaluation function. Therefore, GA-based term selection is performed aiming at the improvement in classification performance on testing sets. In a NSGA-II based term selection method, non-dominated solutions are found. As the result, we can have a set of pareto-optimal solutions. These solutions are helpful to analyze classification results from the viewpoint of terms. From experimental results, we show effectiveness of our proposed term selection methods.

Keywords:

• Nursing-care texts
• Term selection
• Support vector machine
• Genetic algorithm