By Alder M.
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Additional resources for An Introduction to Pattern Recognition
It is not too far fetched to imagine that there are some pain receptors which act on neurons responsible for classifying experiences as `good' and `bad' in a manner essentially similar to what happens in neural nets. But most learning is a more subtle matter than this; a sea anemone `learns' when the tide is coming in without getting a kick in the metaphorical pants. Mistaking a man for a woman or vice versa might be embarrassing, but it is hard to believe you learnt the difference between men and women by making many errors and then reducing the average embarrassment, which is how an artificial neuron of the classical type would do it.
2. will give a second gaussian hill sitting over the female points. The two hills will intersect in some curve, but we shall imagine each of them sitting in place over their respective data points- and also over each others. Let us call them gm and gf for the male and female gaussian functions respectively. If a new data point is provided, we can calculate the height of the two hills at that point, and respectively. It is intuitively appealing to argue that if the male hill is higher than the female hill at the new point, then it is more likely that the new point is male than female.
There are lots of such rules. We consider a few in the next section. Remember that you are supposed to be relaxed and casual at this stage, doing some general thinking and turning matters over in your mind! Can you think, in the light of eggs, potatoes and coffee-cups, of some simple rules for yourself? Next: Decisions, decisions.. html (3 of 3) [12/12/2000 4:03:06 AM] Decisions, decisions.. Next: Metric Methods Up: Basic Concepts Previous: Paradigms Decisions, decisions.. html [12/12/2000 4:03:09 AM] Metric Methods Next: Neural Net Methods (Old Up: Decisions, decisions..
An Introduction to Pattern Recognition by Alder M.