Nearest Neighbor Algorithm
- AKA: Nearest Neighbour Algorithm.
- It can be:
- It can be used by an Instance-based Learning Algorithm.
- a 1-Nearest Neighbor Algorithm.
- a k-Nearest Neighbor Algorithm.
- a Nearest Neighbor Traveling Salesman Algorithm.
- See: Case-based Reasoning Algorithm, Neighbor Relationship.
- (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Nearest_neighbour_algorithm
- The nearest neighbour algorithm was one of the first algorithms used to determine a solution to the travelling salesman problem. It quickly yields a short tour, but usually not the optimal one.
- (Hastie & al, 2009) ⇒ Trevor Hastie, Robert Tibshirani, and Jerome H. Friedman. (2009). "The Elements of Statistical Learning: Data Mining, Inference, and Prediction; 2nd edition." Springer-Verlag. ISBN 0387848576
- (Zezula & al, 2006) ⇒ Pavel Zezula, Giuseppe Amato, Vlastislav Dohnal, and Michal Batko. (2006). "Similarity Search: The Metric Space Approach. Springer, Advances in Database Systems.
- (Mitchell, 1997) ⇒ Tom M. Mitchell. (1997). "Machine Learning." McGraw-Hill.
- QUOTE: Section 8.6 Remarks on Lazy and Eager Learning: In this chapter we considered three lazy learning methods: the k-Nearest Neighbor algorithm, locally weighted regression, and case-based reasoning.
- (Duda & Hart, 1973) ⇒ Richard O. Duda, and Peter E. Hart. (1973). "Pattern Classification and Scene Analysis." John Wiley & Sons, New York, NY.