FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3146056349> ?p ?o ?g. }

• W3146056349 abstract "A systematic study of regression methods for compositional data, which are unique and rare are explored in this thesis. We start with the basic machine learning concept of regression. We use regression equations to solve a classification problem. With partial least squares discriminant analysis (PLS-DA), we follow regression algorithms and solve classification problems, like spam filtering and intrusion detection. After getting the basic understanding of how regression works, we move on to more complex algorithms of distributions based regression. We explore the uni-dimensional case of distributions, applied to regression, the beta-regression. This gives us an understanding of how, when the data to be predicted, or the outcome, is assumed to be of beta distribution, a prediction can be made with regression equations. To further enhance our understanding, we look into Dirichlet distribution, which is for a multi-dimensional case. Unlike traditional regression, here we are predicting a compositional outcome. Two novel regression approaches based on distributions are proposed for compositional data, namely generalized Dirichlet regression and Beta-Liouville regression. They are extensions of Beta regression in a multi-dimensional scenario, similar to Dirichlet regression. The models are learned by maximum likelihood estimation algorithm using Newton-Raphson approach. The performance comparison between the proposed models and other popular solutions is given and both synthetic and real data sets extracted from challenging applications such as market share analysis using Google-Trends and occupancy estimation in smart buildings are evaluated to show the merits of the proposed approaches. Our work will act as a tool for product based companies to estimate how their investments in advertising have yielded results in the market shares. Google-Trends gives an estimate of the popularity of a company, which reflects the effect of advertisements. This thesis bridges the gap between open source data from Google-Trends and market shares." @default.
• W3146056349 created "2021-04-13" @default.
• W3146056349 creator A5042571876 @default.
• W3146056349 date "2019-02-01" @default.
• W3146056349 modified "2023-09-26" @default.
• W3146056349 title "Distributions based Regression Techniques for Compositional Data" @default.
• W3146056349 cites W1481962710 @default.
• W3146056349 cites W1519070426 @default.
• W3146056349 cites W1557577378 @default.
• W3146056349 cites W1569114583 @default.
• W3146056349 cites W1574164692 @default.
• W3146056349 cites W1582684391 @default.
• W3146056349 cites W1968353133 @default.
• W3146056349 cites W1972525513 @default.
• W3146056349 cites W1998643818 @default.
• W3146056349 cites W2001983900 @default.
• W3146056349 cites W2009152144 @default.
• W3146056349 cites W2011275121 @default.
• W3146056349 cites W2029400613 @default.
• W3146056349 cites W2034562813 @default.
• W3146056349 cites W2060556149 @default.
• W3146056349 cites W2062867729 @default.
• W3146056349 cites W2071158874 @default.
• W3146056349 cites W2071189657 @default.
• W3146056349 cites W2082697323 @default.
• W3146056349 cites W2086846349 @default.
• W3146056349 cites W2096177886 @default.
• W3146056349 cites W2100200066 @default.
• W3146056349 cites W2103362801 @default.
• W3146056349 cites W2104969279 @default.
• W3146056349 cites W2111940674 @default.
• W3146056349 cites W2119053066 @default.
• W3146056349 cites W2132446932 @default.
• W3146056349 cites W2134678128 @default.
• W3146056349 cites W2145441622 @default.
• W3146056349 cites W2153796345 @default.
• W3146056349 cites W2157487910 @default.
• W3146056349 cites W2159760567 @default.
• W3146056349 cites W2164583936 @default.
• W3146056349 cites W2166325326 @default.
• W3146056349 cites W2169962072 @default.
• W3146056349 cites W2170902875 @default.
• W3146056349 cites W2186488806 @default.
• W3146056349 cites W2279382301 @default.
• W3146056349 cites W2292427798 @default.
• W3146056349 cites W2323881768 @default.
• W3146056349 cites W2325379241 @default.
• W3146056349 cites W2340809277 @default.
• W3146056349 cites W2475772748 @default.
• W3146056349 cites W25396208 @default.
• W3146056349 cites W2578989670 @default.
• W3146056349 cites W2613514963 @default.
• W3146056349 cites W2885713333 @default.
• W3146056349 cites W2947034755 @default.
• W3146056349 cites W2964212628 @default.
• W3146056349 cites W2971901008 @default.
• W3146056349 cites W3022023470 @default.
• W3146056349 cites W3189081414 @default.
• W3146056349 cites W2185498988 @default.
• W3146056349 hasPublicationYear "2019" @default.
• W3146056349 type Work @default.
• W3146056349 sameAs 3146056349 @default.
• W3146056349 citedByCount "0" @default.
• W3146056349 crossrefType "dissertation" @default.
• W3146056349 hasAuthorship W3146056349A5042571876 @default.
• W3146056349 hasConcept C105795698 @default.
• W3146056349 hasConcept C119857082 @default.
• W3146056349 hasConcept C120068334 @default.
• W3146056349 hasConcept C124101348 @default.
• W3146056349 hasConcept C134306372 @default.
• W3146056349 hasConcept C152877465 @default.
• W3146056349 hasConcept C154945302 @default.
• W3146056349 hasConcept C169214877 @default.
• W3146056349 hasConcept C182310444 @default.
• W3146056349 hasConcept C33923547 @default.
• W3146056349 hasConcept C41008148 @default.
• W3146056349 hasConcept C44882253 @default.
• W3146056349 hasConcept C48921125 @default.
• W3146056349 hasConcept C57381214 @default.
• W3146056349 hasConcept C60316415 @default.
• W3146056349 hasConcept C74127309 @default.
• W3146056349 hasConcept C83546350 @default.
• W3146056349 hasConcept C90157343 @default.
• W3146056349 hasConceptScore W3146056349C105795698 @default.
• W3146056349 hasConceptScore W3146056349C119857082 @default.
• W3146056349 hasConceptScore W3146056349C120068334 @default.
• W3146056349 hasConceptScore W3146056349C124101348 @default.
• W3146056349 hasConceptScore W3146056349C134306372 @default.
• W3146056349 hasConceptScore W3146056349C152877465 @default.
• W3146056349 hasConceptScore W3146056349C154945302 @default.
• W3146056349 hasConceptScore W3146056349C169214877 @default.
• W3146056349 hasConceptScore W3146056349C182310444 @default.
• W3146056349 hasConceptScore W3146056349C33923547 @default.
• W3146056349 hasConceptScore W3146056349C41008148 @default.
• W3146056349 hasConceptScore W3146056349C44882253 @default.
• W3146056349 hasConceptScore W3146056349C48921125 @default.
• W3146056349 hasConceptScore W3146056349C57381214 @default.
• W3146056349 hasConceptScore W3146056349C60316415 @default.
• W3146056349 hasConceptScore W3146056349C74127309 @default.
• W3146056349 hasConceptScore W3146056349C83546350 @default.

• next