By Alder M.
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Makes it clear, in one dimension, that we are just fitting a function to data. 11: A one dimensional pattern recognition problem solved by a neural net. This perspective can be applied to the use of nets in control theory applications, where they are used to learn functions which are not just binary valued. So Supervised Learning is function fitting, while Unsupervised Learning is cluster finding. Both are important things to be able to do, and we shall be investigating them throughout this book.
Html [12/12/2000 4:03:45 AM] Parametric Next: Non-parametric Up: Statistical Methods Previous: Statistical Methods Parametric Returning to the data set of the guys and the gals, you will, if you have had any amount of statistical education (and if you haven't, read up on Information Theory to acquire some), have immediately thought that the cluster of men looked very like what would be described by a bivariate normal or gaussian distribution, and that the cluster of women looked very like another.
One is that we need to compute a comparison with all the data points in the set. This could be an awful lot. , above, where the new point P doesn't look as if it belongs to either category? 3. is a man or a woman would have some advantages, but the metric method needs some modification before it can do this. It is true that P is a long way from the closest point of either category, but how long is a long way? 3 likely to be (a) a kangaroo or (b) a pole vaulter's pole? A more subtle objection would occur only to a geometer, a species of the genus Mathematician.
An Introduction to Pattern Recognition by Alder M.