Performs k-nearest neighbor classification of a test set using a training set. For each row of the test set, the k nearest training set vectors (according to Minkowski distance) are found, and the classification is done via the maximum of summed kernel densities. In addition even ordinal and continuous variables can be predicted.

Performs k-nearest neighbor classification of a test set using a training set. For each row of the test set, the k nearest training set vectors (according to Minkowski distance) are found, and the classification is done via the maximum of summed kernel densities. In addition even ordinal and continuous variables can be predicted.

May 2, 2019 · Performs k-nearest neighbor classification of a test set using a training set. For each row of the test set, the k nearest training set vectors (according to Minkowski distance) are found, and the classification is done via the maximum of summed kernel densities. In addition even ordinal and continuous variables can be predicted. A formula object.

Performs k-nearest neighbor classification of a test set using a training set. For each row of the test set, the k nearest training set vectors (according to Minkowski distance) are found, and the classification is done via the maximum of summed kernel densities.

kknn is a R package for Weighted k-Nearest Neighbors Classification, Regression and Clustering. kknn is licensed under the GPLv2. Weighted k-Nearest Neighbors. Contribute to …

train.kknn returns a list-object of class train.kknn including the components. Matrix of misclassification errors. Matrix of mean absolute errors. Matrix of mean squared errors. List of …

kknn is a R package for Weighted k-Nearest Neighbors Classification, Regression and Clustering. kknn is licensed under the GPLv2.

Weighted k-Nearest Neighbors for Classification, Regression and Clustering. Please use the canonical form https://CRAN.R-project.org/package=kknn to link to this page.

Weighted k-Nearest Neighbors for Classification, Regression and Clustering.

May 2, 2019 · train.kknn returns a list-object of class train.kknn including the components. Matrix of misclassification errors. Matrix of mean absolute errors. Matrix of mean squared errors. List of predictions for all combinations of kernel and k. List containing the …