PARAMETERS OPTIMIZATION OF DECISION TREE AND KNN ALGORITHMS FOR BREAST CANCER PREDICTION

dc.contributor.authorMeraliyev M.M.
dc.contributor.authorOrynbekova K.Ye.
dc.contributor.authorHasanov D.
dc.contributor.authorZhaparov M.K.
dc.date.accessioned2023-10-26T10:11:55Z
dc.date.available2023-10-26T10:11:55Z
dc.date.issued2017
dc.description.abstractAbstract. Throughout the 20th century, views about breast cancer have drastically changed. Breast cancer is the most common cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2012. This type of cancer is the second most common cancer overall. There is lot of information and data, which give opportunity for analyzing some processes, make some researches in classification and in data mining fields, test some tools of machine learning and make experiments for tuning main methods of supervised learning. Main part of project is creating useful tool for predicting breast cancer with high accuracy before getting ill or in initial stage of disease. This work is fascinating because the goal is to implement a lot of tools for creating web system, which can make effective prediction analysis. In other word, we can anticipate the future for women diseases.
dc.identifier.citationM.M. Meraliyev , K.Ye. Orynbekova , D. Hasanov, M.K. Zhaparov / PARAMETERS OPTIMIZATION OF DECISION TREE AND KNN ALGORITHMS FOR BREAST CANCER PREDICTION / СДУ хабаршысы - 2017
dc.identifier.issn2415-8135
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/594
dc.language.isoen
dc.publisherСДУ хабаршысы - 2017
dc.subjectbreast cancer
dc.subjectdiseases prediction
dc.subjectmachine learning methods
dc.subjectscikit
dc.subjectWisconsin Breast Cancer dataset.
dc.subjectСДУ хабаршысы - 2017
dc.subject№2
dc.titlePARAMETERS OPTIMIZATION OF DECISION TREE AND KNN ALGORITHMS FOR BREAST CANCER PREDICTION
dc.typeArticle
dspace.entity.type

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2017.2-185-192.pdf
Size:
273.74 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
13.85 KB
Format:
Item-specific license agreed to upon submission
Description: