Comparative evaluation of accuracy of selected machine learning classification techniques for diagnosis of cancer: a data mining approach

Rajvir Kaur Rajvir Kaur, Jeewani Ginige

Research output: Contribution to journal › Article › peer-review

Original language	Undefined/Unknown
Journal	World Academy of Science, Engineering and Technology: International Journal of Biomedical and Biological Engineering
Publication status	Published - 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

@article{77a465c5fde64f15ae22a10652660263,

title = "Comparative evaluation of accuracy of selected machine learning classification techniques for diagnosis of cancer: a data mining approach",

author = "{Rajvir Kaur}, {Rajvir Kaur} and Jeewani Ginige",

year = "2018",

language = "Undefined/Unknown",

journal = "World Academy of Science, Engineering and Technology: International Journal of Biomedical and Biological Engineering",

}

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Comparative evaluation of accuracy of selected machine learning classification techniques for diagnosis of cancer: a data mining approach

AU - Rajvir Kaur, Rajvir Kaur

AU - Ginige, Jeewani

PY - 2018

Y1 - 2018

M3 - Article

JO - World Academy of Science, Engineering and Technology: International Journal of Biomedical and Biological Engineering

JF - World Academy of Science, Engineering and Technology: International Journal of Biomedical and Biological Engineering

ER -