binary_segmentation: binary_segmentation
In MalteLond/rfcd: Random Forest Change Point Detection

binary_segmentation

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binary_segmentation(x, get_best_split, delta, lambda,
  model_selection_function = NULL, cross_validation_function = NULL,
  control = hdcd_control())

`x`	An n x p data matrix
`get_best_split`	A function with formal arguments `x`, `start`, `end` and `split_candidates` that returns a list with arguments `gain` and `best_split`, where gain is an array of length `nrow(x)` with possibly evaluations of a gains curve or similar saved and `best_split` it the best element of `split_candidates` to split the interval (`start`, `end`].
`delta`	The minimal relative segment length.
`lambda`	A regularisation parameter for methods that require one.
`model_selection_function`	A function with formal arguments `x`, `start`, `split_point` and `end` that returns a list with arguments `statistic`, a value that measures the significance of the split at `split_point`, and `is_siginificant`, a boolean indicating whether the value returned for `statistic` is significant.
`cross_validation_function`	A function with formal arguments `x`, `start`, `end`, `lambda` and `folds` that returns a list with arguments `cv_loss` and `lambda_opt`.
`control`	An object of class `hdcd_control` as generated by hdcd_control.