Prediction Modeling of Boston Crime Data

A comparative study between two supervised learning algorithms, which are decision tree and random forest based on the accuracy and processing time of the models to make predictions using geographical and temporal information provided by splitting the data into training and test sets shows that random forest gives a better result.