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07/26/2023
Emerging Statistical Machine Learning Techniques for Extreme Temperature Forecasting in U.S. Cities
In this paper, we present a comprehensive analysis of extreme temperatur...
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11/04/2022
Improving the Predictive Performances of k Nearest Neighbors Learning by Efficient Variable Selection
This paper computationally demonstrates a sharp improvement in predictiv...
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08/06/2022
Efficient Novelty Detection Methods for Early Warning of Potential Fatal Diseases
Fatal diseases, as Critical Health Episodes (CHEs), represent real dange...
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08/05/2022
A Computational Exploration of Emerging Methods of Variable Importance Estimation
Estimating the importance of variables is an essential task in modern ma...
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01/31/2021
Boosting the Predictive Accurary of Singer Identification Using Discrete Wavelet Transform For Feature Extraction
Facing the diversity and growth of the musical field nowadays, the searc...
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01/31/2021
A Novel Use of Discrete Wavelet Transform Features in the Prediction of Epileptic Seizures from EEG Data
This paper demonstrates the predictive superiority of discrete wavelet t...
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12/07/2020
Nonnegative Matrix Factorization with Zellner Penalty
Nonnegative matrix factorization (NMF) is a relatively new unsupervised ...
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12/07/2020
Nonnegative Matrix Factorization with Toeplitz Penalty
Nonnegative Matrix Factorization (NMF) is an unsupervised learning algor...
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12/20/2019
What do Asian Religions Have in Common? An Unsupervised Text Analytics Exploration
The main source of various religious teachings is their sacred texts whi...
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03/15/2019
Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning
In the monitoring of a complex electric grid, it is of paramount importa...
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11/29/2018
Naive Dictionary On Musical Corpora: From Knowledge Representation To Pattern Recognition
In this paper, we propose and develop the novel idea of treating musical...
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02/20/2018
On the Statistical Challenges of Echo State Networks and Some Potential Remedies
Echo state networks are powerful recurrent neural networks. However, the...
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01/22/2016
A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler
Hierarchical temporal memory (HTM) is an emerging machine learning algor...
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02/16/2015
On the Predictive Properties of Binary Link Functions
This paper provides a theoretical and computational justification of the...
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02/16/2015
Random Subspace Learning Approach to High-Dimensional Outliers Detection
We introduce and develop a novel approach to outlier detection based on ...
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01/25/2015
Prediction Error Reduction Function as a Variable Importance Score
This paper introduces and develops a novel variable importance score fun...
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01/03/2015
A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining
Big data comes in various ways, types, shapes, forms and sizes. Indeed, ...
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10/03/2014