a comprehensive framework for stock price and trend forcasting combining machine learning and deep learning regressores hrough vwhsmsg voting weighted hybrid stacking and manual stacked generalization with technical indicator driven feature engineering

dc.contributor.guide	Dr.J.CHENNI KUMARAN
dc.coverage.spatial
dc.creator.researcher	s.yuvaraj
dc.date.accessioned	2026-02-09T10:16:44Z
dc.date.available	2026-02-09T10:16:44Z
dc.date.awarded	2025
dc.date.completed	2025
dc.date.registered	2022
dc.description.abstract	newline
dc.description.note
dc.format.accompanyingmaterial	None
dc.format.dimensions
dc.format.extent
dc.identifier.researcherid
dc.identifier.uri	http://hdl.handle.net/10603/693779
dc.language	English
dc.publisher.institution	Department of Engineering
dc.publisher.place	Chennai
dc.publisher.university	Saveetha University
dc.relation
dc.rights	university
dc.source.university	University
dc.subject.keyword	Computer Science
dc.subject.keyword	Computer Science Information Systems
dc.subject.keyword	Engineering and Technology
dc.title	a comprehensive framework for stock price and trend forcasting combining machine learning and deep learning regressores hrough vwhsmsg voting weighted hybrid stacking and manual stacked generalization with technical indicator driven feature engineering
dc.title.alternative
dc.type.degree	Ph.D.