RISK PREDICTION OF BREAST CANCER FROM REAL TIME STREAMING HEALTH DATA USING MACHINE LEARNING
| Main Authors: | Mir Junaid Rasool, Amanpreet Singh Brar, Hardeep Singh Kang |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4284315 |
Daftar Isi:
- Background: Mir Junaid Rasool a Computer Science Engineer and Research Student field of interest being Machine learning, Big data science, AI, Web Technologies etc. This article is related to predictive analysis of breast cancer while streams of data is fed continuously in order to perform prediction in real time. The dataset used in this study is “Wisconsin Breast Cancer Data-Set (WBCD)” imported from UCI repository and it needs some preprocessing in order to prepare it for machine learning. In order to carry out this challenge a big data analysis platform which uses in-memory clustering known as Apache Spark can be effectively utilized to monitor data events against machine learning.