Applying Feature Selection to Improve Predictive Performance and Explainability in Lung Cancer Detection With Soft Computing

doi 10.24251/hicss.2020.213
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Hawaii International Conference on System Sciences

Related search

Applying Soft Computing Approaches to River Level Forecasting

Hydrological Sciences Journal
Water ScienceTechnology
1999English

A Feature Selection Model Based on High-Performance Computing (HPC) Techniques

International Journal of Computer Applications
2017English

Performance Comparisons of the Soft Computing Algorithms in Lung Segmentation and Nodule Identification

International Journal of Engineering and Technology(UAE)
ArchitectureHardwareEngineeringChemical EngineeringBiotechnologyEnvironmental EngineeringComputer Science
2017English

Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI

Computational Intelligence and Neuroscience
MedicineMathematicsComputer ScienceNeuroscience
2015English

Applying N-Gram Alignment Entropy to Improve Feature Decay Algorithms

The Prague Bulletin of Mathematical Linguistics
2017English

Covariance Based Outlier Detection With Feature Selection

2016English

Algorithm Fusion to Improve Detection of Lung Cancer on Chest Radiographs

International Journal of Intelligent Computing and Cybernetics
Computer Science
2012English

Distributed Feature Selection(DFS) Strategy for Microarray Gene Expression Data to Improve the Classification Performance

Clinical Epidemiology and Global Health
EpidemiologyPublic HealthMicrobiologyEnvironmentalInfectious DiseasesOccupational Health
2019English

Feature Selection - Extraction Methods Based on PCA and Mutual Information to Improve Damage Detection Problem in Offshore Wind Turbines

Key Engineering Materials
2013English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy