Today in class, we delved into the neighborhood demographics dataset, exploring potential parameters for constructing a time series model. A noteworthy idea emerged: training the model on the last seven decades of data and using it to predict trends for the next one or two decades. Additionally, we delved into another dataset focused on crime incident reports, covering incidents reported in various areas of Boston from 2015 to the present. Notably, the dataset displayed a wide range of values for individual parameters. In our discussion, a proposed approach involved leveraging spatiotemporal analysis to gain insights into the data. The use of spatiotemporal analysis allows for a broader perspective, enabling us to comprehend datasets across larger spatial and temporal ranges. In the upcoming days, I plan to delve into understanding spatiotemporal analysis and integrating it with the crime incident reports dataset for a more comprehensive analysis.

Leave a Reply

Your email address will not be published. Required fields are marked *