package caisar

  1. Overview
  2. Docs
A platform for characterizing the safety and robustness of artificial intelligence based software

Install 

dune-project
 Dependency

git.frama-c.com Readme Changelog Edit opam file Versions (7)

Authors

  1. L
    LAISER team, Software Safety and Security Laboratory, CEA-List

Maintainers

  1. L
    LAISER team, Software Safety and Security Laboratory, CEA-List

Sources

caisar-0.2.1.tbz
sha256=a9a704f1e4e255eee2e9b0333e6c7b0e3e002293ce0068faa1c3d7c18d209997
sha512=7e35bd5527f82c5c6f62452c88e2971907a4eab89fd4efb699b99eb95f730d752908d51c47e104dcff5ceb58cf24c87d3399cb42e09a47691440927463168abb

doc/caisar.xgboost/Caisar_xgboost/Parser/index.html

Module Caisar_xgboost.ParserSource

From https://github.com/dmlc/xgboost/raw/master/doc/model.schema

Sourcetype int_option = int option
Sourceval int_option_none : int32
Sourceval int_option_of_yojson : Yojson.Safe.t -> (int option, string) result
Sourceval int_option_to_yojson : int option -> [> `Intlit of string ]
Sourcetype gbtree_model_param = {
  1. num_trees : string;
  2. num_parallel_tree : string;
  3. size_leaf_vector : string;
}
Sourceand tree_param = {
  1. num_nodes : string;
  2. size_leaf_vector : string;
  3. num_feature : string;
}
Sourceand reg_loss_param = {
  1. scale_pos_weight : string;
}
Sourceand pseudo_huber_param = {
  1. huber_slope : string;
}
Sourceand aft_loss_param = {
  1. aft_loss_distribution : string;
  2. aft_loss_distribution_scale : string;
}
Sourceand softmax_multiclass_param = {
  1. num_class : string;
}
Sourceand lambda_rank_param = {
  1. num_pairsample : string;
  2. fix_list_weight : string;
}
Sourceand tree = {
  1. tree_param : tree_param;
  2. id : int;
  3. loss_changes : float array;
  4. sum_hessian : float array;
  5. base_weights : float array;
  6. left_children : int array;
  7. right_children : int array;
  8. parents : int_option array;
  9. split_indices : int array;
  10. split_conditions : float array;
  11. split_type : int array;
  12. default_left : bool array;
  13. categories : int array;
  14. categories_nodes : int array;
  15. categories_segments : int array;
  16. categories_sizes : int array;
}
Sourceand gbtree = {
  1. gbtree_model_param : gbtree_model_param;
  2. trees : tree array;
  3. tree_info : int array;
}
Sourceand gblinear = {
  1. weights : float array;
}
Sourceand dart = {
  1. gbtree : gbtree;
  2. weight_drop : float array;
}
Sourceand learner_model_param = {
  1. base_score : string;
  2. num_class : string;
  3. num_feature : string;
}
Sourceval show_gbtree_model_param : gbtree_model_param -> Ppx_deriving_runtime.string
Sourceval show_pseudo_huber_param : pseudo_huber_param -> Ppx_deriving_runtime.string
Sourceval show_softmax_multiclass_param : softmax_multiclass_param -> Ppx_deriving_runtime.string
Sourceval show_learner_model_param : learner_model_param -> Ppx_deriving_runtime.string
Sourceval gbtree_model_param_to_yojson : gbtree_model_param -> Yojson.Safe.t
Sourceval tree_param_to_yojson : tree_param -> Yojson.Safe.t
Sourceval reg_loss_param_to_yojson : reg_loss_param -> Yojson.Safe.t
Sourceval pseudo_huber_param_to_yojson : pseudo_huber_param -> Yojson.Safe.t
Sourceval aft_loss_param_to_yojson : aft_loss_param -> Yojson.Safe.t
Sourceval softmax_multiclass_param_to_yojson : softmax_multiclass_param -> Yojson.Safe.t
Sourceval lambda_rank_param_to_yojson : lambda_rank_param -> Yojson.Safe.t
Sourceval tree_to_yojson : tree -> Yojson.Safe.t
Sourceval gbtree_to_yojson : gbtree -> Yojson.Safe.t
Sourceval gblinear_to_yojson : gblinear -> Yojson.Safe.t
Sourceval dart_to_yojson : dart -> Yojson.Safe.t
Sourceval learner_model_param_to_yojson : learner_model_param -> Yojson.Safe.t
Sourcetype gradient_booster =
  1. | Gbtree of gbtree
  2. | Gblinear of gblinear
  3. | Dart of dart
Sourceval gradient_booster_to_yojson : gradient_booster -> [> `Assoc of (string * Yojson.Safe.t) list ]
Sourcetype objective =
  1. | Reg_squarederror of reg_loss_param
  2. | Reg_pseudohubererror of reg_loss_param
  3. | Reg_squaredlogerror of reg_loss_param
  4. | Reg_linear of reg_loss_param
  5. | Binary_logistic of reg_loss_param
Sourceval objective_to_yojson : objective -> [> `Assoc of (string * Yojson.Safe.t) list ]
Sourcetype learner = {
  1. feature_names : string array;
  2. feature_types : string array;
  3. gradient_booster : gradient_booster;
  4. objective : objective;
  5. learner_model_param : learner_model_param;
}
Sourceand t = {
  1. version : int * int * int;
  2. learner : learner;
}
Sourceval learner_to_yojson : learner -> Yojson.Safe.t
Sourceval to_yojson : t -> Yojson.Safe.t
Sourceval _ : Yojson.Safe.t -> t Ppx_deriving_yojson_runtime.error_or