Convex Least Angle Regression Based LASSO Feature Selection and Swish Activation Function Model for Startup Survival Rate

Convex Least Angle Regression Based LASSO Feature Selection and Swish Activation Function Model for Startup Survival Rate

A startup is a recently established business venture led by entrepreneurs, to create and offer new products or services. The discovery of promising startups is a challenging task for creditors, policymakers, and investors. Therefore, the startup survival rate prediction is required to be developed f...

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Bibliographic Details
Main Authors: Allu Ramakrishna, Padmanabhuni Venkata Nageswara Rao
Format: Article
Language:English
Published: Sciendo 2023-11-01
Series:Cybernetics and Information Technologies
Subjects:
convex least angle regression based least absolute shrinkage and selection operator (clar-lasso)
crunch base dataset
startup
survival rate
swish activation function based long short term memory (lstm)
Online Access:https://doi.org/10.2478/cait-2023-0039

Internet

https://doi.org/10.2478/cait-2023-0039

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