Isaac Kofi Nti

Orcid: 0000-0001-9257-4295

According to our database1, Isaac Kofi Nti authored at least 15 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
A Scalable RF-XGBoost Framework for Financial Fraud Mitigation.
IEEE Trans. Comput. Soc. Syst., April, 2024

Empirical assessment of COVID-19 infections and information diffusion: a data science approach.
Int. J. Medical Eng. Informatics, 2024

2023
Predicting diabetes using Cohen's Kappa blending ensemble learning.
Int. J. Electron. Heal., 2023

2022
Applications of artificial intelligence in engineering and manufacturing: a systematic review.
J. Intell. Manuf., 2022

Stacknet based decision fusion classifier for network intrusion detection.
Int. Arab J. Inf. Technol., 2022

A mini-review of machine learning in big data analytics: Applications, challenges, and prospects.
Big Data Min. Anal., 2022

2021
Academic Performance Modelling with Machine Learning Based on Cognitive and Non-Cognitive Features.
Appl. Comput. Syst., 2021

A novel multi-source information-fusion predictive framework based on deep neural networks for accuracy enhancement in stock market prediction.
J. Big Data, 2021

Enhancing Flood Prediction using Ensemble and Deep Learning Techniques.
Proceedings of the 22nd International Arab Conference on Information Technology, 2021

Network Intrusion Detection with StackNet: A phi coefficient Based Weak Learner Selection Approach.
Proceedings of the 22nd International Arab Conference on Information Technology, 2021

2020
Predicting Stock Market Price Movement Using Sentiment Analysis: Evidence From Ghana.
Appl. Comput. Syst., 2020

A comprehensive evaluation of ensemble learning for stock-market prediction.
J. Big Data, 2020

Synchronising social media into teaching and learning settings at tertiary education.
Int. J. Soc. Media Interact. Learn. Environ., 2020

Efficient Stock-Market Prediction Using Ensemble Support Vector Machine.
Open Comput. Sci., 2020

A systematic review of fundamental and technical analysis of stock market predictions.
Artif. Intell. Rev., 2020


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