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Prediction on Heart Disease Data

This task is to predict on a two class problem. The data set contains 304 records, with 13 input variables. The variables were recoded into 28 binary inputs. A comparison was only made between a MLFFN and a modular network because the number of inputs was too small to use a LNN.

The data set was investigated in the project [schm96]. The best result achieved in a long number of tests with the program opti was 88.15%.

Different MNNs using standard parameters (learning parameter η=1, momentum α=0, and the steepness of the activation function λ=1) for learning resulted in a performance of 86%. The training was about four times quicker.


next up previous contents
Next: Prediction on Credit Card Up: Problems with a Small Previous: Prediction on Diabetes Data

Albrecht Schmidt
Mit Okt 4 16:45:34 CEST 2000