activity
20142023
most citedRobust Classification of High Dimension Low Sample Size Data

20 citations · 28 across the 9 of their papers we have counts for

collaborators

9 papers

stat.AP2023

Emerging Statistical Machine Learning Techniques for Extreme Temperature Forecasting in U.S. Cities

Kameron B. Kinast, Ernest Fokoué

In this paper, we present a comprehensive analysis of extreme temperature patterns using emerging statistical machine learning techniques. Our research focuses on exploring and com…

cs.CY2022

Efficient Novelty Detection Methods for Early Warning of Potential Fatal Diseases

Sèdjro Salomon Hotegni, Ernest Fokoué

Fatal diseases, as Critical Health Episodes (CHEs), represent real dangers for patients hospitalized in Intensive Care Units. These episodes can lead to irreversible organ damage a…

stat.ML2022

A Computational Exploration of Emerging Methods of Variable Importance Estimation

Louis Mozart Kamdem, Ernest Fokoue

Estimating the importance of variables is an essential task in modern machine learning. This help to evaluate the goodness of a feature in a given model. Several techniques for est…

cs.SD20157 cited

A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs

Zichen Ma, Ernest Fokoue

An algorithm involving Mel-Frequency Cepstral Coefficients (MFCCs) is provided to perform signal feature extraction for the task of speaker accent recognition. Then different class…

math.ST2015

An Information-Theoretic Alternative to the Cronbach's Alpha Coefficient of Item Reliability

Ernest Fokoue, Necla Gunduz

We propose an information-theoretic alternative to the popular Cronbach alpha coefficient of reliability. Particularly suitable for contexts in which instruments are scored on a st…

stat.AP20151 cited

Pattern Discovery in Students' Evaluations of Professors: A Statistical Data Mining Approach

Necla Gunduz, Ernest Fokoue

The evaluation of instructors by their students has been practiced at most universities for many decades, and there has always been a great interest in a variety of aspects of the…