Using artificial intelligence in analyzing principal components

Abstract

In this research, the basic concepts of both principal component analysis and artificial neural networks were reviewed, let alone tackling breast cancer, its most important causes and early detection. To add more, obtaining the principal components of a set of explanatory variables using the artificial neural network method was also discussed. One of the most important conclusions reached is that the weights of the artificial neural network based on the (Hebb) rule are close to the values ??of the characteristic vectors for the correlation matrix. The flexibility of the work of artificial neural networks allows for the expansion of the use of neural networks in other statistical methods. The most important factors causing breast cancer are: marital status, age and breastfeeding, and family history of the disease.