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Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Frontiers

Enhanced risk prediction of femoral head osteonecrosis in the elderly: a comparative study of random forest and logistic regression models

Department of Orthopedics, Shanxi Bethune Hospital, Tongji Shanxi Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Taiyuan, China Background and aim: ...
IEEE

An Improved Iterative Learning Control Approach Based on Random Forest and Whale Optimization for Urban Traffic Signals

Abstract: Iterative learning control (ILC) has demonstrated effectiveness in urban traffic signal control systems. However, conventional ILC methods typically require infinite iterations to achieve ...
pv magazine International

Surplus PV for electric delivery vehicles

Researchers from Japan's Waseda University have developed a new model that optimizes the route of electric delivery vehicles (EDVs) to maximize local PV surplus usage. For this purpose, the academics ...
Scientific Research Publishing

He, S., Wu, J., Wang, D., & He, X. (2022). Predictive Modeling of Groundwater Nitrate Pollution and Evaluating Its Main Impact Factors Using Random Forest. Chemosphere, 290 ...

ABSTRACT: An integrated model approaching to combining the BETR-GLOBAL model with a Random Forest method was developed in this research. Firstly, the BETR-GLOBAL model was employed to simulate the ...
Scientific Research Publishing

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
IEEE

Factor Screening for Equivalence Ratio Measurement Modeling: A Hybrid Approach Integrating Random Forest Algorithm and Support Vector Regression

Abstract: Measuring the equivalence ratio using flame spectral data is a key focus in combustion diagnostic techniques. Traditional methods rely on chemiluminescent bands with distinct spectral ...
Frontiers

Toward the Prediction of Multi-Spin State Charges of a Heme Model by Random Forest Regression

Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China The random forest regression (RFR) model was introduced to predict the ...