PhilArchive
open access
Study and Performance Evaluation of Machine Learning Algorithms
In the fields of computer science and artificial intelligence, machine learning has emerged as one of the most significant and quickly developing technologies. This paper describes several machine learning algorithms. Data mining, image processing, predictive analytics, healthcare, cyber security, recommendation systems, and natural language processing are just a few of the many uses for these techniques. The main advantage of using machine learning is that algorithms can do jobs independently with little assistance from humans once they have learned how to use data. The accuracy, efficiency, training time, scalability, and prediction capabilities of various machine learning algorithms are compared and evaluated in this research report.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Machine Learning#490985
- Machine learning#126955
- Machine learning#18330
- Machine Learning#10774
- Machine Learning#3547
Record · ID 1505583
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive