CCI (version 0.3.6)

wrapper_xgboost: Extreme Gradient Boosting wrapper for CCI

Description

Extreme Gradient Boosting wrapper for CCI

Usage

wrapper_xgboost(
  formula,
  data,
  train_indices,
  test_indices,
  metric,
  nrounds = 500,
  metricfunc = NULL,
  nthread = 1,
  eps = 1e-15,
  subsample = 1,
  ...
)

Value

Performance metric

Arguments

formula

Model formula

data

Data frame

train_indices

Indices for training data

test_indices

Indices for training data

metric

Type of metric ("RMSE", "Kappa" or "Log Loss")

nrounds

Number of boosting rounds

metricfunc

A user specific metric function which have the arguments data, model test_indices and test_matrix and returns a numeric value

nthread

Integer. Number of threads to use for parallel computation during model training in XGBoost. Default is 1.

eps

Small value to avoid log(0) in LogLoss calculations. Default is 1e-15.

subsample

Numeric. The proportion of the data to be used for subsampling. Default is 1 (no subsampling).

...

Additional arguments passed to xgb.train