Paper Info
Title
Beta-Liouville Regression And Applications
Abstract
A novel regression algorithm has been proposed, Beta-Liouville regression, to solve regression of compositional data, where the prediction is multi-dimensional and sums to unity. Applications include market-share data mining in relation to its score in Google-trends and smart building occupancy estimation. The study of Google-trends in relation to market-shares gives a good estimate of whether the company's investment in advertisements have yielded any results in improving their market-shares. Secondly, occupant behaviour in buildings gives useful insights on the required levels of air conditioning, lighting and even initiating help during emergency. Sensors to estimate the occupancy of a smart building include microphone, door/window positions, motion detection, power consumption. The Beta-Liouville regression algorithm is compared to ordinary least squares regression with compositional transformations and Dirichlet regression.
Year
DOI
Venue
2019
10.1109/CoDIT.2019.8820449
2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019)
Field
DocType
ISSN
Data mining,Motion detection,Regression,Computer science,Compositional data,Ordinary least squares,Occupancy,Building automation,Dirichlet distribution,Microphone
Conference
2576-3555
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Divya Ankam100.34
Nizar Bouguila21539146.09
Manar Amayri304.39