Difference between revisions of "K-Nearest Neighbors (KNN)"
| Line 13: | Line 13: | ||
* [http://www.unite.ai/what-is-k-nearest-neighbors/ What Is K-Nearest Neighbors? | Daniel Nelson - Unite.ai] | * [http://www.unite.ai/what-is-k-nearest-neighbors/ What Is K-Nearest Neighbors? | Daniel Nelson - Unite.ai] | ||
| − | Can be used for | + | Can be used for regression or classification by choosing 'K'; where 'K' = # of closest neighboring data points that the model uses in prediction. |
This is a simple algorithm which predicts unknown data point with its k nearest neighbors. The value of k is a critical factor here regarding the accuracy of prediction. It determines the nearest by calculating the distance using basic distance functions like Euclidean. However, this algorithm needs high computation power and we need to normalize data initially to bring every data point to same range. [http://towardsdatascience.com/10-machine-learning-algorithms-you-need-to-know-77fb0055fe0 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium] | This is a simple algorithm which predicts unknown data point with its k nearest neighbors. The value of k is a critical factor here regarding the accuracy of prediction. It determines the nearest by calculating the distance using basic distance functions like Euclidean. However, this algorithm needs high computation power and we need to normalize data initially to bring every data point to same range. [http://towardsdatascience.com/10-machine-learning-algorithms-you-need-to-know-77fb0055fe0 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium] | ||
Revision as of 13:50, 26 April 2020
YouTube search... ...Google search
Can be used for regression or classification by choosing 'K'; where 'K' = # of closest neighboring data points that the model uses in prediction.
This is a simple algorithm which predicts unknown data point with its k nearest neighbors. The value of k is a critical factor here regarding the accuracy of prediction. It determines the nearest by calculating the distance using basic distance functions like Euclidean. However, this algorithm needs high computation power and we need to normalize data initially to bring every data point to same range. 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium
