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8 results for Homicide

Study analyzes homicide rates in Goias, Brazil, using clustering methods.

problem Understanding spatial distribution and risk factors of homicide in Goias.
method Cluster analysis using K-means, Density-based, and Hierarchical algorithms.
result Homicide rates higher in cities near large urban centers despite better socioeconomic indicators.

Machine learning predicts homicide clearance rates with SHAP explaining key features.

problem Predicting and explaining homicide clearance rates in the US.
method Nine algorithmic approaches compared; XGBoost selected. SHAP used for feature importance.
result XGBoost best predicts national homicide clearance rates; SHAP reveals key features.

Causal discovery algorithms can help generate legal arguments.

problem Leveraging causal discovery algorithms in legal decision-making.
method Prepared a legal dataset, annotated with 17 legal concepts, applied causal discovery algorithms, and quantified degrees of belief.
result Some causal relationships help generate viable legal arguments.

Understanding the causes of crime is a longstanding issue in researcher's agenda. While it is a hard task to extract causality from data, several linear models have been proposed to predict crime through the existing correlations between crime and urban metrics. However, because of non-Gaussian distributions and multic…

2017-12-08abs ↗pdf ↗