In data science competitions and machine learning projects, we often may encounter geospatial features that are (most of the time) represented as longitude and latitude.
These kinds of features will influence your predictive model’s results by a large margin if they aren’t well represented; therefore, these features are seldom considered, and they’re often eliminated from the feature’s set.
Continue reading Working with Geospatial Data in Machine Learning