Review of random forest classification techniques to resolve data imbalance

Data Imbalance ◽

Effectiveness of Random Forest Classification Techniques for Feature Selection on a Large Extra Corporeal Membrane Oxygenation Dataset

American Journal of Clinical Pathology ◽

10.1093/ajcp/144.suppl2.175 ◽

2015 ◽

Vol 144 (suppl 2) ◽

pp. A175-A175

Author(s):

James Szymanski ◽

Ivo Francischetti

Keyword(s):

Feature Selection ◽

Random Forest ◽

Extra Corporeal Membrane Oxygenation ◽

Membrane Oxygenation ◽

2012 IEEE International Conference on Computational Intelligence and Cybernetics (CyberneticsCom) ◽

Cancer disease prediction with support vector machine and random forest classification techniques

10.1109/cyberneticscom.2012.6381608 ◽

2012 ◽

Cited By ~ 1

Author(s):

K Ashfaq Ahmed ◽

Sultan Aljahdali ◽

Nisar Hundewale ◽

K Ishthaq Ahmed

Keyword(s):

Support Vector Machine ◽

Random Forest ◽

Support Vector ◽

Disease Prediction ◽

Cancer Disease ◽

Breast Cancer Tumor Categorization using Logistic Regression, Decision Tree and Random Forest Classification Techniques

International Journal of Research in Arts and Science ◽

10.9756/bp2019.1002/27 ◽

2019 ◽

Vol 5 (Special Issue) ◽

pp. 282-289

Author(s):

Dr. Akila A ◽

Ms. Padma R

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Random Forest ◽

Decision Tree ◽

Forest Classification ◽

Cancer Tumor

Comparative Prediction Performance with Support Vector Machine and Random Forest Classification Techniques

International Journal of Computer Applications ◽

10.5120/11885-7922 ◽

2013 ◽

Vol 69 (11) ◽

pp. 12-16 ◽

Cited By ~ 2

Author(s):

Ashfaq AhmedK ◽

Sultan Aljahdali ◽

Syed Naimatullah Hussain

Keyword(s):

Support Vector Machine ◽

Random Forest ◽

Prediction Performance ◽

Support Vector ◽

Epilepsy Detection Using Random Forest Classification Based on Locally Linear Embedding Algorithm

2020 5th International Conference on Control, Robotics and Cybernetics (CRC) ◽

10.1109/crc51253.2020.9253455 ◽

2020 ◽

Author(s):

Qing Hou ◽

Yang Liu ◽

Jun Liu ◽

Siqi Sun

Keyword(s):

Random Forest ◽

Locally Linear Embedding ◽

Forest Classification ◽

Linear Embedding ◽

Locally Linear

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Experimental Eye Research ◽

10.1016/j.exer.2015.09.011 ◽

2016 ◽

Vol 146 ◽

pp. 370-385 ◽

Cited By ~ 10

Author(s):

Adam Hedberg-Buenz ◽

Mark A. Christopher ◽

Carly J. Lewis ◽

Kimberly A. Fernandes ◽

Laura M. Dutca ◽

...

Keyword(s):

Random Forest ◽

Ganglion Cell ◽

Retinal Ganglion Cell ◽

Quantitative Measurement ◽

Cell Populations ◽

Retinal Ganglion ◽

Chronic Kidney Disease for Collaborative Healthcare Data Analytics using Random Forest Classification Algorithms

2021 International Conference on Computer Communication and Informatics (ICCCI) ◽

10.1109/iccci50826.2021.9402574 ◽

2021 ◽

Author(s):

V. Shanmugarajeshwari ◽

M. Ilayaraja

Keyword(s):

Chronic Kidney Disease ◽

Random Forest ◽

Kidney Disease ◽

Data Analytics ◽

Classification Algorithms ◽

Healthcare Data ◽

Spatial sampling effect on data structure and Random Forest classification of tissue types in High Definition and Standard Definition FT-IR imaging

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2021.104407 ◽

2021 ◽

pp. 104407

Author(s):

Danuta Liberda ◽

Karolina Kosowska ◽

Paulina Koziol ◽

Tomasz P. Wrobel

Keyword(s):

Data Structure ◽

Random Forest ◽

Spatial Sampling ◽

High Definition ◽

Standard Definition ◽

Sampling Effect ◽

Forest Classification ◽

Ft Ir

Random forest classification of salt marsh vegetation habitats using quad-polarimetric airborne SAR, elevation and optical RS data

Remote Sensing of Environment ◽

10.1016/j.rse.2014.04.010 ◽

2014 ◽

Vol 149 ◽

pp. 118-129 ◽

Cited By ~ 108

Author(s):

Sybrand van Beijma ◽

Alexis Comber ◽

Alistair Lamb

Keyword(s):

Salt Marsh ◽

Random Forest ◽

Salt Marsh Vegetation ◽

Marsh Vegetation ◽

Forest Classification ◽

Airborne Sar

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Environmental Monitoring and Assessment ◽

10.1007/s10661-015-4489-3 ◽

2015 ◽

Vol 187 (5) ◽

Cited By ~ 46

Author(s):

Vahid Eisavi ◽

Saeid Homayouni ◽

Ahmad Maleknezhad Yazdi ◽

Abbas Alimohammadi

Keyword(s):

Random Forest ◽

Land Cover ◽

Land Cover Mapping ◽

Thermal Images ◽