KNEARST - NEIGHBOR ALGORITHM ANALYSIS USING SIMPLE LINIER REGRESSION MODELING

1*I Gusti Prahmana, Dr. Herman Mawengkang, Dr. Muhammad Zarlis

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Abstract:

A process to explain the results of the KNN algorithm analysis with prediction of Breast Cancer Coimbra (KNN algorithm) output results will be added with the modeling of the Simple Linear Regression algorithm to measure predictive data through a straight line as an illustration of the correlation between 2 or more variables. Linear regression prediction, is used as a technique for the relationship of variables in the prediction process of the Breast Cancer Coimbra data set. for the K value in analyzing the KNN algorithm take the nearest neighbor with the results of the ranking with K = 5 the nearest neighbor taken in the KNN calculation. Which is where the results of the KNN algorithm classification results will be analyzed by the Simple Linear Regression algorithm with Dependent (Cause) and Independent (effect) variables. The test results are 97% accurate. It is that by using algorithmic analysis by modeling Simple Linear Regression to determine patients affected by breast cancer and the number of predictions based on age with glucose, the patient is predicted to have breast cancer. analyze the KNN algorithm with Simple Liner Regression modeling with Python programming language.

Keywords:

K - Nearest Neighbor, Simple Linear Regression, Breast Cancer Coimbra

Paper Details
Month4
Year2020
Volume24
IssueSpecial Issue 2
Pages283-287