Skip to content

PostProcessors Practical Guide

PostProcessors are processors which occours after predicitons. Full PostProcessor code doc: https://Medial-EarlySign.github.io/MR_LIBS/classPostProcessor.html Some PostProcessor, for full list of types and json values to put in names please reffer to PostProcessor_Types. ·          We have now MultiPostProcessor (for parallelism) ·          Calibrator – to calibrate scores to probabilities for example ·          ModelExplainer – Several options for ButWhy:   PostProcessor API:   ModelExplainer API:   Examples:

  • Calibration
  • Explainer of prediction "But Why"   Example for calibration: 
    1
2
3
4
5
6
7
8
9
    {
      "action_type":"post_processor",
      "pp_type":"calibrator",
      "calibration_type":"binning",
      "min_preds_in_bin":"200",
      "min_prob_res":"0.005",
      //"calibration_samples":"", //on train or give your samples to calibrate on
      "verbose":"1"
}
    Example for explainer:   Tree Shapley: 
    1
2
3
4
5
6
    {
      "action_type":"post_processor",
      "pp_type":"tree_shap",
      "approximate":"0",
      "interaction_shap":"0"
}
    LIME: 
    1
2
3
4
5
6
7
8
9
    {
      "action_type":"post_processor",
      "pp_type":"lime_shap",
      //"pp_type":"shapley",
      "gen_type":"GIBBS",
      "n_masks":"500", //how many masks to sample for learn
      "generator_args":"{kmeans=0;select_with_repeats=0;max_iters=0;predictor_type=qrf;predictor_args={spread=0;type=categorial_entropy;learn_nthreads=40;predict_nthreads=40;ntrees=50;maxq=500;min_node=300;get_only_this_categ=-1};num_class_setup=n_categ;bin_settings={split_method=iterative_merge;min_bin_count=500;binCnt=150};selection_ratio=1.0}", //when using Gibbs, otherwise give GAN path here
      "sampling_args":"{burn_in_count=50;jump_between_samples=10;samples_count=1;find_real_value_bin=1;use_cache=0}" //in GAN not needed
}