The feature-value paradox: Unsupervised discovery of strategic archetypes in the smartphone market using machine learning
This study employs unsupervised machine learning, a core branch of Artificial Intelligence (AI), and feature importance analysis to identify strategic archetypes in the smartphone market based solely on technical specifications. Moving be- yond traditional price prediction models, we analyze a comprehensive dataset to discover latent product strategies. Using K-Means clustering, we identify five distinct strategic […]
Automated COVID-19 detection from chest X-rays using HOG features
The COVID-19 pandemic has necessitated the development of rapid and accurate diagnostic tools to assist healthcare professionals in disease detection and management [1]. This study presents a different machine learning framework for COVID-19 classification using chest X-ray images, employing Histogram of Oriented Gradients (HOG) feature extraction combined with Principal Component Analysis (PCA) for dimensionality reduction […]
Development and evaluation of an effective machine learning model for well log prediction: A case study of sonic log prediction of zircon field Niger-Delta Nigeria
The accurate prediction of sonic log data is critical for subsurface characterization and reservoir management in hydrocarbon exploration. Conventional methods of predicting missing well logs which often relied on interpolation techniques or empirical correlations are limited in their ability to capture the complex, nonlinear relationships that exist in subsurface formations. In this study we present […]