TY - JOUR

T1 - Regression from distributed data sources using discrete neighborhood representations and modified stalked generalization models

AU - Allende-Cid, Héctor

AU - Allende, Héctor

AU - Monge, R.

AU - Moraga, Claudio

N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015

PY - 2015

Y1 - 2015

N2 - In this work we present a Distributed Regression approach, which works in problems where distributed data sources may have different contexts. Different context is defined as the change of the underlying law of probability in the distributed sources. We present an approach which uses a discrete representation of the probability density functions (pdfs). We create neighborhoods of similar datasets, comparing their pdfs, and use this information to build an ensemble-based approach and to improve a second level model used in this proposal, that is based in stalked generalization. We compare the proposal with other state of the art models with 5 real data sets and obtain favorable results in the majority of the datasets.

AB - In this work we present a Distributed Regression approach, which works in problems where distributed data sources may have different contexts. Different context is defined as the change of the underlying law of probability in the distributed sources. We present an approach which uses a discrete representation of the probability density functions (pdfs). We create neighborhoods of similar datasets, comparing their pdfs, and use this information to build an ensemble-based approach and to improve a second level model used in this proposal, that is based in stalked generalization. We compare the proposal with other state of the art models with 5 real data sets and obtain favorable results in the majority of the datasets.

KW - Context-aware regression

KW - Distributed machine learning

KW - Similarity representation

UR - http://www.scopus.com/inward/record.url?scp=84921463067&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-10422-5_27

DO - 10.1007/978-3-319-10422-5_27

M3 - Article

AN - SCOPUS:84921463067

SN - 1860-949X

VL - 570

SP - 249

EP - 258

JO - Studies in Computational Intelligence

JF - Studies in Computational Intelligence

ER -