Host: The Japanese Society for Artificial Intelligence
Name : The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, 2019
Number : 33
Location : [in Japanese]
Date : June 04, 2019 - June 07, 2019
The purpose of this research is to clarify the difference of the characteristics of independent component analysis and factor analysis. We focus on the rotation criterion of these two methods this paper. we clarified the relationship between Crawford and Ferguson criterion used in factor analysis and kurtosis criterion used in independent component analysis. Moreover, we found that the characteristics of the kurtosis criterion that emphasizes the simplification of rows of a factor loading matrix because the relationship between Crawford and Ferguson criterion and kurtosis criterion. We can make the same rotation as the kurtosis criterion by changing the weights of Crawford and Ferguson criterion. Experimental using sample data showed the relationship between this kurtosis criterion and Crawford and Ferguson criterion and the characteristics of kurtosis.