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License: GNU General Public License v3.0
Decompose gbm predictions into feature contributions
License: GNU General Public License v3.0
Example from decompose_gbm_prediction function results in the following error; Error in decompose_gbm_prediction(gbm1, data[1, ]) : βNAβ is not an expected level for X4
Add function to verify feature contributions against prediction from gbm.
Plot single tree in model and show decision path for an observation through the tree.
Add an example with pictures (output table + tree path) to README.md and #16
Complete documentation for all functions.
No option to specify a subset of tree to use in the model.
Need to add functionality to deal with predictions returned on link scale (poisson + bernoulli distributions)
Ordered factors have var.type = 0 so are compared as; value >= split point. This results in an NA as value is a factor level and _split point_is numeric. This then errors the surrounding if statement.
Output results in table with the following columns; variable, variable value, prediction contribution
Add links to other similar packages
Toy gbm from examples in help files fails the validate_decomposition function.
Add tree and node indexes to the split decision info returned.
Write tests for functions
Add overall package documentation.
Sometimes when running the example from decompose_gbm_prediction function the following error occurs; Error in if (!num_value == pred_row[[split_col_name]]) { : missing value where TRUE/FALSE needed ....
Try re running the function a few times to replicate
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