I am trying to compute the accuracy of the HMAX model. I am using the Face category (containing 435 images) from the Caltech101 database. I split it into x training and y testing. At each time, when x increases, the accuracy also increases. Furthermore, I heard that the number of training should be equal to 80% by comparing it to the tests. So when I split my data into 348 positive training and the rest for positive testing, I got an accuracy that it is smaller than the other smaller splits (when x<348)!!.
Even when I took x=300, I also got a smaller accuracy!!
By the way, I also used the background category and I split it into 50 negative training and 50 negative testing.
Please why I got a smaller accuracy? Please I need your help.