Current Slide

• k-NN for real-valued prediction for a given unknown tuple
• Returns the mean values of the k nearest neighbors
• Distance-weighted nearest neighbor algorithm
• Weight the contribution of each of the k neighbors according to their distance to the query xq

\[ w=\frac{1}{d(x_{q}, x_{i})^2} \]

• Give greater weight to closer neighbors
• Robust to noisy data by averaging k-nearest neighbors
• Curse of dimensionality: distance between neighbors could be dominated by irrelevant attributes
• To overcome it, axes stretch or elimination of the least relevant attributes