{"repository":{"description":"This project presents a hybrid algorithm for training RBF network based on K-means and SOM. The algorithm consists of a proposed clustering algorithm to position the RBF center and givens least squares to estimate the weights. The aim of this experiment is to recognize printed digits (1-4) using the hybrid model. In the meanwhile, KNN and MLP with Scaled Conjugate Gradient will be implemented in order to show the comparative of different models according to the experiments.","watchers":0,"stargazers":0,"forks":0,"fork":false,"size":530,"owner":"shenzhun","private":false,"open_issues":0,"has_issues":true,"has_downloads":true,"has_wiki":true,"language":"Matlab","created_at":"2013-08-25T01:41:19-07:00","pushed_at":"2013-08-25T01:52:05-07:00","master_branch":"master"},"actor_attributes":{"type":"User","name":"Shen Zhun","company":"IBM","blog":"http：//shenzhun.github.io","location":"China","email":"173fbc94689d3063bc173520aa802d452c1468e6@gmail.com"},"url":"https://github.com/shenzhun/printed-digits-classification/compare/4ffdfcf1b3...b4a68b678b"}