Saturday 19th May

May have been a bit hasty declaring I had preprocessed all the data. I have been looking at the statistical analysis of the data today and have identified an number of rules. After having read through the T396 project I have decided to handle uncertainty using certainty factors as I seem to ba able to understand this more than fuzzy logic and baysian updating. After the statistical analysis I have decided that I will not use all the possible attributes as input neurons for the neural network.

For example there seems to be no significance between the location of the tumour in the breast and the chances of reccurence of the tumour, apart from a much lower incidence of reccurence if the tumour is located centrally. Therefore I will cut this down from 5 input neurons (one for each quadrant) to 2 input neurons (central or not). There are several other possible situations where the number of input neurons could be reduced.

I hope to very shortly complete the rules identification. I have four rules that are always true and the rest are mostly true so will need to be used with the certainty factors.

As an aside and worth remembering when discussing this project is that there is no indication of how long was it from when the tumour was removed to the assessment of whether there was reccurence or not, i.e. if the patients without reccurence were followed up a few years later would the tumour still not have reoccured.