I'm trying to train a neural network using this sort of data (for a homework): Number of Features : 42, Target data : 0 or 1, Number of Samples : 111 Individuals ( 69 Cases + 42 Controls )
However i'm facing an over-learning issue (the learning curve approaches the goal set, however the validation curve shows no improvement): the learning stops after less than 15 iterations because of a great number of validation fails: no improvement in the quality of validation tests. I managed to have great results by using 444 (4*111) examples in my training as I repeated the initial data four times. but i'm not sure if this is clean. In other words, is it alright to repeat existing examples to have more values for training ?
Thanks in advance.