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Published in:
Classifying Human Activities with Temporal Extension of Random Forest Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Modeling the Propensity Score with Statistical Learning

Authors : Kenshi Uchihashi, Atsunori Kanemura

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

The progress of the ICT technology has produced data-sources that continuously generate datasets with different features and possibly with partial missing values. Such heterogeneity can be mended by integrating several processing blocks, but a unified method to extract conclusions from such heterogeneous datasets would bring consistent results with lower complexity. This paper proposes a flexible propensity score estimation method based on statistical learning for classification, and compared its performance against classical generalized linear methods.

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Metadata
Title
Modeling the Propensity Score with Statistical Learning
Authors
Kenshi Uchihashi
Atsunori Kanemura
Copyright Year
2016
Book
Neural Information Processing

Print ISBN: 978-3-319-46680-4

Electronic ISBN: 978-3-319-46681-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-46681-1_32

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