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ISSN 2996-8380
Astronomy
Vol. Scholarly Debut, Issue Spring 2026, 2026March 30, 2026 CEST

A Machine Learning Method for Classifying Variable Stars

Shreenidhi Anand, Sahasra Lugudu,
Machine learningGradient BoostingRandom ForestVariable starsCepheidRR Lyrae.
Copyright Logoccby-4.0 • https://doi.org/10.70121/001c.158326
Photo by Jeremy Thomas on Unsplash

Articles in Vol. Scholarly Debut, Issue Spring 2026, 2026

Vol. Scholarly Debut, Issue Spring 2026, 2026
  • Advancing Suicide-Risk Detection in Post-COVID Hospital Systems: A Three-Layer Model for Unified Screening, Training, and Follow-Up
    Lidya Gondere
  • Fantasy Urbanism: Theme Parks as Blueprints for Better Cities
    Irene Yitan Xue
  • Voice-Controlled Vehicle: Determining the Best Machine Learning Models for Voice Recognition
    Dhruv Panchagatti
  • Multiple Paths to Healing: A Narrative Review of Hippocratic, Traditional Chinese, Ayurvedic, and Modern Western Medical Traditions
    Elaina Huang
  • The Greenest Air Filters: Impact of Urban Green Spaces on Air Quality
    Danny Xu
  • A Machine Learning Method for Classifying Variable Stars
    Shreenidhi AnandSahasra Lugudu
  • Localized Chemotherapy with Carmustine (BCNU) Wafers in High-Grade Gliomas: Clinical Outcomes and Safety Review
    David Hu
Scholarly Review Journal
Anand, Shreenidhi, and Sahasra Lugudu. 2026. “A Machine Learning Method for Classifying Variable Stars.” Scholarly Review Journal Scholarly Debut (Spring 2026). https://doi.org/10.70121/001c.158326.
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