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TreeIG 0.2.2

  • GitHub
  • GitHub

Documentation

User guide

  • Getting started
  • Worked examples
  • Choosing baselines and batching
  • Supported models
  • Reading and plotting results
  • Explaining loss reduction
  • Attribution and interpretation
  • TreeIGNumeric
  • Performance and repeated calls
  • TreeIG and TreeSHAP
  • GPUTreeIG: optional CUDA execution
  • The Integrated Gradients Stack

Reference

  • API reference
  • References and citation
  • Building the documentation
  • Publishing releases

Index

A | B | C | D | E | L | M | N | S | T | W

A

  • attribute() (treeig.TreeIG method)

B

  • backend (treeig.TreeIG attribute)

C

  • compute() (in module treeig)
  • compute_numeric() (in module treeig)

D

  • diagnostics() (treeig.TreeIG method)
    • (treeig.TreeIGNumeric method)

E

  • explain() (treeig.TreeIG method)
    • (treeig.TreeIGNumeric method)
  • Explanation (class in treeig)

L

  • loss_attribution() (treeig.TreeIG method)

M

  • max_abs_completeness_error (treeig.Explanation property)
  • model (treeig.TreeIG attribute)
  • model_output() (treeig.TreeIG method)
    • (treeig.TreeIGNumeric method)
  • multiclass_loss_attribution() (treeig.TreeIG method)

N

  • n_features_in_ (treeig.TreeIG attribute)

S

  • supports() (in module treeig)

T

  • to_shap() (treeig.Explanation method)
  • trace() (treeig.TreeIG method)
  • TreeIG (class in treeig)
  • TreeIGNumeric (class in treeig)

W

  • warmup() (treeig.TreeIG method)

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