JICS

1. Anomaly detection and attack type classification mechanism using Extra Tree and ANN

Min-Gyu Kim, Myung-Mook Han, Vol. 23, No. 5, pp. 79-85, Oct. 2022

10.7472/jksii.2022.23.5.79
Keywords: Extreme Random Forest, Artificial neural network, Anomaly Detection, Anomaly Detection and Attack type Classification, Network intrusion detection

2. Exploring the Predictive Variables of Government Statistical Indicators on Retail sales Using Machine Learning: Focusing on Pharmacy

Gwang-Su Lee, Vol. 23, No. 3, pp. 125-135, Jun. 2022

10.7472/jksii.2022.23.3.125
Keywords: Machine Learning, Random Forest, XGBoost, LightGBM, CatBoost, Government Statistical Indicators

3. A research on the emotion classification and precision improvement of EEG(Electroencephalogram) data using machine learning algorithm

Hyunju Lee, Dongil Shin, Dongkyoo Shin, Vol. 20, No. 5, pp. 27-36, Oct. 2019

10.7472/jksii.2019.20.5.27
Keywords: DEAP dataset, ICA, Arousal-Valence plane, Random Forest, Attribute Selected Classifier

4. The prediction of appearance of jellyfish through Deep Neural Network

CHEOLHUN HWANG, Myung-Mook Han, Vol. 20, No. 5, pp. 1-8, Oct. 2019

10.7472/jksii.2019.20.5.1
Keywords: deep neural network, Bootstrapping, Data Expansion, Transfer Learning, Random Forest, Sequence Forward Selection

5. Research on improving correctness of cardiac disorder data classifier by applying Best-First decision tree method

Hyun-Ju Lee, Dong-Kyoo Shin, Hee-Won Park, Soo-Han Kim, Dong-Il Shin, Vol. 12, No. 6, pp. 63-72, Dec. 2011
Keywords: ECG, classifier, R-R interval, SVM, MLP, Random Forest, B-F Tree, Accuracy

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