By Soumen Chakrabarti, et al
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Example text
But actually the number of possible rule sets is finite. 2 this involves four terms in all. Because the number of possible rules is finite, the number of possible rule sets is finite, too, although extremely large. However, we’d hardly be interested in sets that contained a very large number of rules. In fact, we’d hardly be interested in sets that had more rules than there are examples because it is difficult to imagine needing more than one rule for each example. So if we were to restrict consideration to rule sets smaller than that, the problem would be substantially reduced, although still very large.
2 Bias Viewing generalization as a search in a space of possible concepts makes it clear that the following are most important decisions in a machine learning system. 30 CHAPTER 1 What’s It All About? The concept description language. The order in which the space is searched. n The way that overfitting to the particular training data is avoided. n n These three properties are generally referred to as the bias of the search and are called language bias, search bias, and overfitting-avoidance bias.
The order in which the space is searched. n The way that overfitting to the particular training data is avoided. n n These three properties are generally referred to as the bias of the search and are called language bias, search bias, and overfitting-avoidance bias. You bias the learning scheme by choosing a language in which to express concepts, by searching in a particular way for an acceptable description, and by deciding when the concept has become so complex that it needs to be simplified.
