Classifiers

Training data can be geometrically illustrated. Example: linear classifier.

Training Error

If the classifier classifies correctly 50% of the points, it misses 50% (training error \varepsilon_n(h) ) in the test data set, it’s equal to chance.

Hypothesis Space

Since each classifier represents a possible “hypothesis” regarding the data, the set of all possible classifiers could be viewed as the space of possible hypotheses.

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