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Linear iterative feature embedding an ensemble framework for an interpretable model

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Bibliographic Details
Main Authors: Agus, Sudjianto, Jinwen, Qiu, Miaoqi, Li
Format: Book
Language:English
Published: Springer 2023
Subjects:
LIFE
FFNN
Online Access:https://link.springer.com/article/10.1007/s00521-023-08204-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8311
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spelling oai:localhost:PNK-83112023-04-26T02:37:50Z Linear iterative feature embedding an ensemble framework for an interpretable model Agus, Sudjianto Jinwen, Qiu Miaoqi, Li LIFE FFNN CC BY A new ensemble framework for an interpretable model called linear iterative feature embedding (LIFE) has been developed to achieve high prediction accuracy, easy interpretation, and efficient computation simultaneously. The LIFE algorithm is able to fit a wide single-hidden-layer neural network (NN) accurately with three steps: defining the subsets of a dataset by the linear projections of neural nodes, creating the features from multiple narrow single-hidden-layer NNs trained on the different subsets of the data, combining the features with a linear model. The theoretical rationale behind LIFE is also provided by the connection to the loss ambiguity decomposition of stack ensemble methods. Both simulation and empirical experiments confirm that LIFE consistently outperforms directly trained single-hidden-layer NNs and also outperforms many other benchmark models, including multilayers feed forward neural network (FFNN), Xgboost, and random forest (RF) in many experiments. As a wide single-hidden-layer NN, LIFE is intrinsically interpretable. Meanwhile, both variable importance and global main and interaction effects can be easily created and visualized. In addition, the parallel nature of the base learner building makes LIFE computationally efficient by leveraging parallel computing. 2023-04-26T02:37:50Z 2023-04-26T02:37:50Z 2023 Book https://link.springer.com/article/10.1007/s00521-023-08204-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/8311 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic LIFE
FFNN
spellingShingle LIFE
FFNN
Agus, Sudjianto
Jinwen, Qiu
Miaoqi, Li
Linear iterative feature embedding an ensemble framework for an interpretable model
description CC BY
format Book
author Agus, Sudjianto
Jinwen, Qiu
Miaoqi, Li
author_facet Agus, Sudjianto
Jinwen, Qiu
Miaoqi, Li
author_sort Agus, Sudjianto
title Linear iterative feature embedding an ensemble framework for an interpretable model
title_short Linear iterative feature embedding an ensemble framework for an interpretable model
title_full Linear iterative feature embedding an ensemble framework for an interpretable model
title_fullStr Linear iterative feature embedding an ensemble framework for an interpretable model
title_full_unstemmed Linear iterative feature embedding an ensemble framework for an interpretable model
title_sort linear iterative feature embedding an ensemble framework for an interpretable model
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00521-023-08204-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8311
_version_ 1764268033395654656
score 8.891145

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