A graph based regression model from flat unstructured dataset. Each line in the input data set is treated as a node from which an edge to another line (node) can be formed. In the training process, a model is created which contains sparse graph adjacency matrix. This model is then used for prediction by taking a predictor and the model as inputs and outputs a prediction which is an average of the most similar node and its neighbours in the model graph.
|Depends:||R (≥ 3.2.4)|
|Imports:||stringr, igraph, KRLS, caTools, mclust, caret, stats, graphics|
|Maintainer:||Yossi Keshet <jossiekat at icloud.com>|
|CRAN checks:||kinn results|
|Windows binaries:||r-devel: kinn_0.2.zip, r-release: kinn_0.2.zip, r-oldrel: kinn_0.2.zip|
|OS X Mavericks binaries:||r-release: kinn_0.2.tgz, r-oldrel: kinn_0.2.tgz|
|Old sources:||kinn archive|
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