The Use of Feature Engineering and Hyperparameter Tuning for Machine Learning Accuracy Optimization: A Case Study on Heart Disease Prediction
C Herdian, S Widianto, JA Ginting, YM Geasela… - … Applications of Artificial …, 2024 - Springer
Heart disease (Cardiovascular) illness presents a noteworthy public health issue and ranks
among the primary factors contributing to mortality worldwide. The World Health …
among the primary factors contributing to mortality worldwide. The World Health …
Predicting the Conversion from Clinically Isolated Syndrome to Multiple Sclerosis in Mexican Mestizo Patients Using Gaussian Naive Bayes Classifier: A Prospective …
NK Yulinda - International Journal of Artificial Intelligence in …, 2024 - jurnal.yoctobrain.org
This study explores the application of the Gaussian Naive Bayes (GNB) classifier to predict
the conversion from Clinically Isolated Syndrome (CIS) to Multiple Sclerosis (MS) among …
the conversion from Clinically Isolated Syndrome (CIS) to Multiple Sclerosis (MS) among …
Performance Evaluation of Machine Learning Algorithms in Predicting Global Warming: A Comparative Study of Random Forest, K-Nearest Neighbors and Support …
A Putri, R Martiansah, QFF Safiesza… - … : Indonesian Journal of …, 2024 - journal.irpi.or.id
Global Warming is a global warming phenomenon that has a significant impact on human
health and the environment. This research aims to apply Machine Learning algorithms …
health and the environment. This research aims to apply Machine Learning algorithms …
ANALISIS PERBANDINGAN PERFORMA APP ENGINE DAN COMPUTE ENGINE PADA GOOGLE CLOUD PLATFORM DALAM MEMPREDIKSI PENYAKIT MATA …
IPTK Wiranata, AAII Paramitha… - JATI (Jurnal Mahasiswa …, 2023 - ejournal.itn.ac.id
Abstract Menurut data Perhimpunan Dokter Spesialis Mata Indonesia (PERDAMI)
menyatakan bahwa penyebab kebutaan tertinggi di Indonesia disebabkan oleh penyakit …
menyatakan bahwa penyebab kebutaan tertinggi di Indonesia disebabkan oleh penyakit …
[引用][C] Perbandingan Algoritma Naive Bayes Dan K-Nearest Neighbor Terhadap Analisis Sentimen Aplikasi Rosalia Indah Transport
H Satrio, EK Pratama