Explanatory model analysis: explore, explain, and examine predictive models

By:

Biecek, Przemyslaw

Contributor(s):

Burzykowski, Tomasz

Material type: Text

TextSeries: Chapman & Hall/CRC Data Science SeriesPublication details: CRC Press Boca Raton 2021Description: xiii, 309 pISBN:

9780367693923

Subject(s):

DDC classification:

511.8 BIE

Summary: Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems. (https://www.routledge.com/Explanatory-Model-Analysis-Explore-Explain-and-Examine-Predictive-Models/Biecek-Burzykowski/p/book/9780367693923]

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	511.8 BIE (Browse shelf(Opens below))	1	Available		006658

Table of content:
1. Introduction.

2. Prediction Understanding.

3. Model Understanding.

4. Model Fidelity.

5. Other Topics.
[https://www.routledge.com/Explanatory-Model-Analysis-Explore-Explain-and-Examine-Predictive-Models/Biecek-Burzykowski/p/book/9780367693923]

Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.
(https://www.routledge.com/Explanatory-Model-Analysis-Explore-Explain-and-Examine-Predictive-Models/Biecek-Burzykowski/p/book/9780367693923]

There are no comments on this title.

to post a comment.