Implementation:Interpretml Interpret ExportableEBMModel

Field	Value
Sources	Repo: InterpretML
Domains	Reporting, Interpretability
Updated	2026-02-07

Overview

Concrete tool for exporting a fitted EBM to an Excel workbook with embedded charts provided by the InterpretML library.

Description

The ExportableEBMModel class creates an Excel workbook using xlsxwriter. After initialization with a fitted EBM and output path, calling generate() creates Overview, Variables, and Evaluation worksheets with embedded matplotlib/seaborn charts. Calling save() writes the workbook to disk.

Usage

Use this when generating audit-ready Excel reports from trained EBM models.

Code Reference

Field	Value
Source	interpretml/interpret
File	python/interpret-core/interpret/glassbox/_ebm/_excel.py
Lines	1870-1985

Signature:

class ExportableEBMModel:
    def __init__(self, ebm_model, output_file: str, author: str = "", date_stamp: str = ""):
    def generate(self) -> None:
    def save(self) -> None:

Import:

from interpret.glassbox._ebm._excel import ExportableEBMModel

I/O Contract

Init Inputs:

Parameter	Type	Required	Description
ebm_model	fitted EBM	Yes	A fitted ExplainableBoostingClassifier or ExplainableBoostingRegressor instance
output_file	str	Yes	File path for the output .xlsx file
author	str	No	Author name for the report metadata
date_stamp	str	No	Date stamp for the report metadata

generate() Outputs:

Type	Description
None	Creates worksheets in memory

save() Outputs:

Type	Description
None	Writes .xlsx file to disk at the specified output_file path

Usage Examples

from interpret.glassbox import ExplainableBoostingClassifier
from interpret.glassbox._ebm._excel import ExportableEBMModel

ebm = ExplainableBoostingClassifier()
ebm.fit(X_train, y_train)

exporter = ExportableEBMModel(ebm, "model_report.xlsx", author="Data Science Team")
exporter.generate()
exporter.save()

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