Hyperparameters
=================
K=1: Number of neighbors weights=:uniform: Either :uniform or :distance based weights of
the neighbors. - :uniform: All neighbors are weighted equally. - :distance: Each
neighbor is weighted by it's distance. distance=DTW(): DTW distance struct, for example
DTWSakoeChiba or pure DTW. - DTW(): Dynamic Time Warping without any constraints. -
DTWSakoeChiba(): Dynamic Time Warping with Sakoe Chiba bound constraint. - DTWItakura():
Dynamic Time Warping without Itakura Parallelogram constraint. - You can provide your
own metric by subtyping DTWType. bounding=LBNone(): Lower bounding of the distance using
methods like LBKeogh(). - LBNone(): NO-OP, no lower bouning is being done. - LBKeogh():
Estimating distance lower bound of the distance using the LB_Keogh method
(https://www.cs.ucr.edu/~eamonn/LB_Keogh.htm). - You can provide your own methofs by
subtyping LBType.
Part of the output from
?KNNDTWModel
: