sharkpy.explaining

Attributes

`_create_temp_plot`(→ str)	Create a temporary plot and return its path
`_add_table_to_doc`(doc, df, title)	Helper function to add a pandas DataFrame as a table to DOCX
`_add_metrics_table_to_doc`(doc, cv_results, train_metrics)	Add performance metrics table to DOCX document
`_export_deep_explanation_docx`(docx_path, ...[, depth])	Export explanation to DOCX with specified depth level
`_convert_docx_to_pdf`(docx_path, pdf_path)	Convert DOCX to PDF using docx2pdf
`_get_data_insights`(features, target, target_name, ...)	Extract dynamic insights from the data
`explain_model`(model, features, target, target_name[, ...])	Generate model explanation with customizable depth and export options
`demo_explanation`()	Demo the explanation system

sharkpy.explaining._create_temp_plot(model, features, target, kind: str, width: int = 8, height: int = 6) → str[source]: Create a temporary plot and return its path

sharkpy.explaining._add_table_to_doc(doc: docx.Document, df: pandas.DataFrame, title: str)[source]: Helper function to add a pandas DataFrame as a table to DOCX

sharkpy.explaining._add_metrics_table_to_doc(doc: docx.Document, cv_results, train_metrics)[source]: Add performance metrics table to DOCX document

sharkpy.explaining._export_deep_explanation_docx(docx_path, deep_explanation, model, features, target, feature_df, depth='deep')[source]: Export explanation to DOCX with specified depth level

sharkpy.explaining._convert_docx_to_pdf(docx_path, pdf_path)[source]: Convert DOCX to PDF using docx2pdf

sharkpy.explaining._get_data_insights(features, target, target_name, data, label_encoder, is_regression)[source]: Extract dynamic insights from the data

sharkpy.explaining.explain_model(model, features, target, target_name, data=None, label_encoder=None, cv_results=None, train_metrics=None, export_path=None, format='txt', depth='deep')[source]: Generate model explanation with customizable depth and export options