A quantitative study of experimental neural network learning algorithm evaluation practices

113 articles about neural network learning algorithms published in 1993 and 1994 are examined for the amount of experimental evaluation they contain. Every third of them does employ not even a single realistic or real learning problem. Only 6% of all articles present results for more than one problem using real world data. Furthermore, one third of all articles does not present any quantitative comparison with a previously known algorithm. These results indicate that the quality of research in the area of neural network learning algorithms needs improvement. The publication standards should be raised and easily accessible collections of example problems be built.