Learn about cross validation in Python with data from the Adult Census Income dataset (1996) /

This dataset is designed for teaching the cross validation in machine learning. The dataset is a subset of data derived from the 1996 Adult Census Income dataset, and the example demonstrates how to use the cross validation to search for optimal values for user-specified parameters when using random...

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Bibliographic Details
Main Author:	Shi, Feng, active 2019 (Author)
Corporate Author:	Odum Institute (Author)
Format:	eBook
Language:	English
Published:	London : SAGE Publications, Ltd., 2019.
Subjects:	Regression analysis. Machine learning. Income. Python (Computer program language) Regression Analysis Income Machine Learning Analyse de régression. Apprentissage automatique. Revenu. Python (Langage de programmation) Machine learning Regression analysis
Online Access:	Connect to the full text of this electronic book

Description
Summary:	This dataset is designed for teaching the cross validation in machine learning. The dataset is a subset of data derived from the 1996 Adult Census Income dataset, and the example demonstrates how to use the cross validation to search for optimal values for user-specified parameters when using random forest to predict annual income class with individual features such as demographics, working status, marital status, etc. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Python.
Physical Description:	1 online resource : illustrations
Bibliography:	Includes bibliographical references and index.
ISBN:	9781526498892 1526498898