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PERBANDINGAN ANALISIS DISKRIMINAN LINIER DAN REGRESI LOGISTIK MULTINOMIAL DALAM KLASIFIKASI PENYAKIT JANTUNG PADA DATA MULTIKELAS
In inferential statistics, linear discriminant analysis and multinomial logistic regression are methods used for multiclass categorical data classification. Linear discriminant analysis aims to construct linear combinations of independent variables that maximize separation between classes and minimize within-class variation. Meanwhile, multinomial logistic regression is used to model the relationship between a categorical dependent variable with more than two classes and one or more independent variables, whether numerical or categorical. This study uses secondary data on the severity level of heart disease obtained from Kaggle, consisting of 202 respondents. The dependent variable is the level of heart disease severity, categorized into five groups: 0 (normal), 1 (mild), 2 (moderate), 3 (severe), dan 4 (very severe). The independent variables included in this study are age (
FAKULTAS SYARIAH DAN HUKUM, UIN SUNAN KALIJAGA YOGYAKARTA
NIM.: 22106010031 Nurul Hanin Azzahra Supriyono
PERBANDINGAN ANALISIS DISKRIMINAN LINIER DAN REGRESI LOGISTIK MULTINOMIAL DALAM KLASIFIKASI PENYAKIT JANTUNG PADA DATA MULTIKELAS (Text)
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