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Publications by Tom Howley
The Effect of Principal Component Analysis on Machine Learning Accuracy With High Dimensional Spectral Data
A Machine Learning Application for Classification of Chemical Spectra
Classification of a Target Analyte in Solid Mixtures Using Principal Component Analysis, Support Vector Machines, and Raman Spectroscopy
Related publications
Principal Component Analysis for Sparse High-Dimensional Data
Lecture Notes in Computer Science
Computer Science
Theoretical Computer Science
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
Applied Mathematics
Computer Vision
Mathematics
Computational Theory
Artificial Intelligence
Software
High-Dimensional Data Classification Based on Principal Component Analysis Dimension Reduction and Improved BP Algorithm
DEStech Transactions on Computer Science and Engineering
Statistical Machine Learning for Spectral Data Analysis
Materia Japan
Enforcement of the Principal Component Analysis–extreme Learning Machine Algorithm by Linear Discriminant Analysis
Neural Computing and Applications
Artificial Intelligence
Software
Dimensionality Reduction of High-Dimensional Data With a NonLinear Principal Component Aligned Generative Topographic Mapping
SIAM Journal of Scientific Computing
Computational Mathematics
Applied Mathematics
Research on Network Intrusion Detection Based on Incremental Extreme Learning Machine and Adaptive Principal Component Analysis
Energies
Control
Electronic Engineering
Energy Engineering
Renewable Energy
Energy
Fuel Technology
Sustainability
Optimization
Electrical
Power Technology
the Environment
Robust Principal Component Analysis of Data With Missing Values
Lecture Notes in Computer Science
Computer Science
Theoretical Computer Science
Nonlinear Regression With High-Dimensional Space Mapping for Blood Component Spectral Quantitative Analysis
Journal of Spectroscopy
Optics
Analytical Chemistry
Atomic
Spectroscopy
Molecular Physics,
