Open AccessPENERAPAN ALGORITMA REGULARIZED DISCRIMINANT ANALYSIS UNTUK KLASIFIKASI KANKER PARU
Author(s) -
Evy Priyanti
Publication year - 2020
Publication title -
ilmu komputer, manajemen dan sosial swabumi : suara wawasan sukabumi/swabumi (suara wawasan sukabumi)
Language(s) - English
Resource type - Journals
eISSN - 2549-5178
pISSN - 2355-990X
DOI - 10.31294/swabumi.v8i2.8386
Subject(s) - linear discriminant analysis , mathematics , quadratic classifier , discriminant , optimal discriminant analysis , kernel fisher discriminant analysis , pattern recognition (psychology) , lung cancer , artificial intelligence , generalization , statistics , computer science , medicine , pathology , mathematical analysis , support vector machine , facial recognition system
Lung cancer is a type of cancer that starts from the lungs with abnormal cell growth. Lung cancer is a type of cancer with the largest number of sufferers. In this research, Regularized Discriminant Analysis (RDA) analysis is used to classify the types of lung cancer that exist. Regularized Discriminant Analysis (RDA) is a generalization of Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA). If the alpha parameter is set to 1, this operator performs an LDA. Likewise if the alpha parameter is set to 0, this operator performs QDA. Discriminant analysis is used to determine which variables distinguish between two or more groups that occur naturally. With an accuracy value of 60%, it can be ascertained the type of lung cancer suffered by patients for ease of care and treatment.