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- K-Nearest Neighbors Density Estimation931 B (124 words) - 09:55, 22 January 2015
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- **Density Estimation with K-Nearest Neighbors (KNN) ***[[K-Nearest Neighbors Density Estimation|Video slecture in English]] by Qi Wang <span style="colo10 KB (1,450 words) - 19:50, 2 May 2016
- ...e the density for each point to be classified. Parzen window and K-nearest neighbors (KNN) are two of the famous non-parametric methods. Two common concerns abo ...><math>\widehat{\mathbf{\Sigma}} = \frac{1}{N}\sum_{k=1}^{N}(x_{k}-\mu)(x_{k}-\mu)^{T}</math><br></center>7 KB (1,177 words) - 09:47, 22 January 2015
- K-Nearest Neighbors Density Estimation This slecture discusses about the K-Nearest Neighbors(k-NN) approach to estimate the density of a given distribution.10 KB (1,743 words) - 09:54, 22 January 2015
- K Nearest Neighbors K Nearest Neighbors is a classification algorithm based on local density estimation.9 KB (1,604 words) - 09:54, 22 January 2015
- <font size="4">From KNN to Nearest Neighbor Classification </font> .... In this tutorial, we will explain first the concept of KNN, secondly the nearest neighbor approach, and thirdly discuss briefly the comparative advantages a6 KB (1,013 words) - 09:55, 22 January 2015
- K-Nearest Neighbors Density Estimation931 B (124 words) - 09:55, 22 January 2015
- *Density Estimation with K-Nearest Neighbors (KNN) **[[K-Nearest Neighbors Density Estimation|Video slecture in English]] by Qi Wang8 KB (1,123 words) - 09:38, 22 January 2015