M.C.A. SEM V MCA 52: Artificial Intelligence.pdfl
Garcia Miller
First, we would like to stress the general limitations of artificial intelligence based techniques such as the overfitting and the data specific local optima problems. However, the specific comments brought by the author are not applicable in our case. First, studies on the number of events per predictor are applicable for logistic regressions (LRs) which is not used in the SPOT algorithm. In fact, our results show poor LR performance which is consistent with the rule of thumb of 1 to 10 referred to by the author. Hence, while serving as a good guidance for LR, the rule is not binding and more importantly it does not guarantee the generalization of the learned model. To further illustrate, classification models using convolutional neural networks have millions of parameters and are trained with datasets that, in most cases, do not have millions of samples in each group. However, these models have acceptable generalization capabilities and are tested using the data-split method. In SPOT, the model at its core is a regressi...