tabular_trees.validate_monotonic_constraints

tabular_trees.validate_monotonic_constraints(tabular_trees, constraints, return_detailed_results=False)

Validate that trees conform to monotonic constraints.

Parameters:

• tabular_trees (TabularTrees) – Trees to check.

• constraints (dict[str, int]) – Monotonic constraints to check. Should be dict where keys give variable names and values are either -1 for monotonic decreasing constraint and 1 for monotonic increasing constraint.

• return_detailed_results (bool, defualt=False) – Should detailed breakdown of every split be returned?

Returns:

results – Object containing results of checking monotonic trends.

Return type:

MonotonicConstraintResults

Examples

>>> import xgboost as xgb
>>> import pandas as pd
>>> from sklearn.datasets import load_diabetes
>>> from tabular_trees import export_tree_data
>>> from tabular_trees.validate import validate_monotonic_constraints
>>> # get data in DMatrix
>>> diabetes = load_diabetes()
>>> data = xgb.DMatrix(
...     diabetes["data"],
...     label=diabetes["target"],
...     feature_names=diabetes["feature_names"]
... )
>>> # define monotonic constraints
>>> feature_names = diabetes["feature_names"]
>>> constraints = pd.Series([0] * len(feature_names), index=feature_names)
>>> constraints.loc[constraints.index.isin(["bmi", "s5"])] = -1
>>> constraints.loc[constraints.index.isin(["bp", "age"])] = 1
>>> constraints_dict = constraints.loc[constraints != 0].to_dict()
>>> # build model
>>> params = {
...     "max_depth": 3,
...     "verbosity": 0,
...     "monotone_constraints": tuple(constraints)
... }
>>> model = xgb.train(params, dtrain=data, num_boost_round=10)
>>> # export to TabularTrees
>>> xgboost_tabular_trees = export_tree_data(model)
>>> tabular_trees = xgboost_tabular_trees.to_tabular_trees()
>>> # check monotonic constraints
>>> validate_monotonic_constraints(tabular_trees, constraints=constraints_dict)
... 
MonotonicConstraintResults(summary={'age': True, 'bp': True, 's5': True},
    constraints={'age': 1, 'bmi': -1, 'bp': 1, 's5': -1},
    all_constraints_met=True)