Results 31 to 40 of about 5,175,696 (290)

Feature selection for modular GA-based classification [PDF]

, 2004
Genetic algorithms (GAs) have been used as conventional methods for classifiers to adaptively evolve solutions for classification problems. Feature selection plays an important role in finding relevant features in classification.
Anand, Battiti, Brameier, Falco, Fangming Zhu, Gonzalez, Guan, Guan, Ishibuchi, Jenkins, Kwak, Lerner, Lu, Pal, Setiono, Setnes, Steven Guan, Verikas   +17 more
core   +1 more source

A Framework to Discover Emerging Patterns for Application in Microarray Data [PDF]

, 2003
Various supervised learning and gene selection methods have been used for cancer diagnosis. Most of these methods do not consider interactions between genes, although this might be interesting biologically and improve classification accuracy.
Boulesteix, Anne-Laure, Tutz, Gerhard
core   +3 more sources

A new pathophysiological concept and new classification of pre-eclampsia [PDF]

Vojnosanitetski Pregled, 2018
nema
Mirković Ljiljana, Nejković Lazar, Micić Jelena   +2 more
doaj   +1 more source

Hierarchical incremental class learning with reduced pattern training [PDF]

, 2006
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but closer examination reveals areas for potential improvement.
Bao, C, Guan, SU, Sun, RT
core   +1 more source

Secure Multi-Party Computation Based Privacy Preserving Extreme Learning Machine Algorithm Over Vertically Distributed Data

, 2015
Especially in the Big Data era, the usage of different classification methods is increasing day by day. The success of these classification methods depends on the effectiveness of learning methods.
Çatak, Ferhat Özgür
core   +1 more source

Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results [PDF]

, 2012
In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject.
Amorim, Renato, Gan, John Q, Mirkin, Boris   +2 more
core   +1 more source

News Location Classification

iRASD Journal of Computer Science and Information Technology, 2021
Every day there are a lot of things that happen around the world. There are various ways to record every event that is occurring around the world, such as news, blogs, and articles. Over the past few years, there are multiple news available on every event that has occurred.
Malik Shahzad Ahmad, Muhammad Azhar Bhatti   +1 more
openaire   +1 more source

Morphological variability of the piriformis muscle

Folia Morphologica
BACKGROUND: The aim of the study is to create several classifications of the piriformis muscle (PM): proximal and distal attachments, potential fusions, and the relationship with the sciatic nerve.
Łukasz Olewnik, Nicol Zielinska, Kacper Ruzik, Michał Podgórski, Krzysztof Koptas, Piotr Karauda, Adrian Balcerzak, Bartosz Gonera, Richard Shane Tubbs   +8 more
doaj   +1 more source

Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image [PDF]

, 2017
As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral image (HSI) classification, the recognition rate is too low. This is because
Cao, Faxian, Jiang, Mengying, Ling, Wing-Kuen, Ren, Jinchang, Yang, Zhijing   +4 more
core   +3 more sources

SCOPe: Structural Classification of Proteins--extended, integrating SCOP and ASTRAL data and classification of new structures. [PDF]

, 2013
Structural Classification of Proteins-extended (SCOPe, http://scop.berkeley.edu) is a database of protein structural relationships that extends the SCOP database.
Brenner, Steven E, Chandonia, John-Marc, Fox, Naomi K   +2 more
core   +2 more sources