Feature selection and feature extraction in pattern analysis: A literature review

B Ghojogh, MN Samad, SA Mashhadi, T Kapoor… - ar**.pdf" data-clk="hl=en&sa=T&oi=gga&ct=gga&cd=5&d=6970199345304059902&ei=h3usZ7njHJuoieoP4-_VmAI" data-clk-atid="_j-C9l8fu2AJ" target="_blank">[PDF] rug.nl

A general framework for dimensionality-reducing data visualization map**

K Bunte, M Biehl, B Hammer - Neural Computation, 2012 - ieeexplore.ieee.org
In recent years, a wealth of dimension-reduction techniques for data visualization and
preprocessing has been established. Nonparametric methods require additional effort for …

Predicting financial distress in the Indian banking sector: A comparative study between the logistic regression, LDA and ANN models

N Mishra, S Ashok, D Tandon - Global Business Review, 2024 - journals.sagepub.com
Financial distress is a socially and economically significant issue that affects almost every
firm across the world. Predicting financial distress in the banking industry can substantially …

Deepview: Visualizing classification boundaries of deep neural networks as scatter plots using discriminative dimensionality reduction

A Schulz, F Hinder, B Hammer - arxiv preprint arxiv:1909.09154, 2019 - arxiv.org
Machine learning algorithms using deep architectures have been able to implement
increasingly powerful and successful models. However, they also become increasingly more …

Dimensionality reduction for data visualization [applications corner]

S Kaski, J Peltonen - IEEE signal processing magazine, 2011 - ieeexplore.ieee.org
Dimensionality reduction is one of the basic operations in the toolbox of data analysts and
designers of machine learning and pattern recognition systems. Given a large set of …

Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data

K Bunte, B Hammer, A Wismüller, M Biehl - Neurocomputing, 2010 - Elsevier
Due to the tremendous increase of electronic information with respect to the size of data sets
as well as their dimension, dimension reduction and visualization of high-dimensional data …