Machine Learning: Algorithms and Applications
By Mohssen M. Z. E. Mohammed, Muhammad Badruddin Khan, Eihab B. M. Bashier. 2016
332 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/37b7096e8818ee9b12034a0023268d590bf65810
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Computer Networks and Communications
- Tao Huang
- Fotios Zantalis
- Renchao Xie
- Jun-feng Xie
- F. Yu
- Sotiris Karabetsos
- Dionisis Kandris
- Yun-jie Liu
In Information Systems
Citations in the corpus
- Smart Transportation: An Overview of Technologies and Applications (2023, methodology): “It involves categorizing the sample data by quantifiable properties known as features, and an ML algorithm attempts to identify a relationship between the features and specific output values known as labels [69].”
- A Review of Machine Learning and IoT in Smart Transportation (2019, background): “It works mostly like the unsupervised learning with the improvements that a portion of labeled data can bring [8].”
- Review of Wearable Devices and Data Collection Considerations for Connected Health (2021, methodology): “Pattern matching has also been used in a wide range of data science applications, such as Natural Language Processing, spam filtering, digital libraries and web search engines [139].”
- A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges (2019, background): “ing theory and its classical concepts, please refer to [73]–[76].”