To classify something, find things that are similar and label it with the same class as the most similar thing.
The feature space is \(N-d\), where \(N\) is the number of features. Each instance is mapped to a point. The descriptive features become the axes.
The Similarity Metric Mathematically, it must conform to these 4 criteria:
Non-negative: \(f(a, b) \ge 0\) Identity: \( f(a, b) = 0 \iff a = b \) Symmetry: \( f(a, b) = f(b, a) \) Triangular inequality: \( f(a, b) \le f(a, c) + f(c, b) \) Why are non-negativity and triangular inequality important?...

To classify something, find things that are similar and label it with the same class as the most similar thing.
The feature space is \(N-d\), where \(N\) is the number of features. Each instance is mapped to a point. The descriptive features become the axes.
The Similarity Metric Mathematically, it must conform to these 4 criteria:
Non-negative: \(f(a, b) \ge 0\) Identity: \( f(a, b) = 0 \iff a = b \) Symmetry: \( f(a, b) = f(b, a) \) Triangular inequality: \( f(a, b) \le f(a, c) + f(c, b) \) Why are non-negativity and triangular inequality important?...