Description Usage Arguments Value See Also Examples
View source: R/IterativeQuantileNearestNeighbors.R
Function for creating iterative quantile nearest neighbors model. Bin the training data, then store the binning definitions and bin statistics to be used to estimate for future testing data.
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data |
Data frame containing the response variable and numeric input variables from the training data |
y |
Name of response variable column |
mod_type |
Depends on response variables type: "reg" creates iqnn-regression for predicting numeric values, "class" creates iqnn-classifier for predicting categorical values |
bin_cols |
vector of column names of variables to iteratively bin, ordered first to last |
nbins |
vector of number of bins per step of iterative binning, ordered first to last |
jit |
vector of margins for uniform jitter to each dimension to create seperability of tied obs due to finite precision |
stretch |
TRUE/FALSE if will bins be given tolerance buffer |
tol |
vector of tolerance values to stretch each dimension for future binning |
list containing binned training data, binning definition, and bin statistics
Other iterative quantile nearest-neighbors functions: iqnn_cv_predict
,
iqnn_predict
, iqnn_tune
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