Machine Learning Approaches to Predict Crime Rate in the City of Los Angeles
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Poster presentation exploring crime rate prediction in Los Angeles using multiple machine learning algorithms.
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Poster presentation exploring crime rate prediction in Los Angeles using multiple machine learning algorithms.
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End-to-end pipeline for loan-approval prediction: EDA, interaction diagnostics, LASSO feature selection with 5-fold CV, thresholding to control FPR.
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Comparative analysis of OLS, WLS, and ARIMA models to forecast U.S. Used Vehicle CPI. The study identifies ARIMA(0,1,2) as the optimal model for short-term prediction, outperforming macroeconomic regression approaches.
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Hierarchical Beta-Binomial model implemented in JAGS to estimate serious crime probabilities across 21 LAPD areas, using Gibbs sampling to stabilize estimates for high-variance districts.
Published in 2023 International Conference on Education, Management, Economics and Social Science (ICEMESS 2023), 2023
This study employs wavelet coherence analysis to uncover the dynamic interdependence between geopolitical risk, policy uncertainty, oil prices, and global stock markets during the Russo-Ukrainian War.
Recommended citation: R. Zhang, Y. Shi, and X. Song (2023). "Wavelet Coherence Approach Linking Russo-Ukrainian War, Oil Prices, Geopolitical Risk, Stock Market, and Policy Uncertainty in the Global Economy." *Proceedings of the 2023 International Conference on Education, Management, Economics and Social Science (ICEMESS 2023)*. DOI: 10.23977/ICEMESS2023.114.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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