In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study

In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study

Background: The advancement of big data analytics calls for careful selection of processing frameworks to optimize machine learning effectiveness. Choosing the appropriate framework can significantly influence the speed and accuracy of data analysis, ultimately leading to more informed decision maki...

Full description

Saved in:
Bibliographic Details
Main Authors: Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale
Format: Article
Language:English
Published: Prague University of Economics and Business 2025-08-01
Series:Acta Informatica Pragensia
Online Access:https://aip.vse.cz/artkey/aip-202503-0010_in-memory-versus-disk-based-computing-with-random-forest-for-stock-analysis-a-comparative-study.php
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items