Predicting geographic events
I'm new to Rapidminer and predictive analytics and I'm attempting to build a model that can predict the likelihood of an event occurring within an area based on years of previous data.
I have several years of data of these events including their lat/long and numerous characteristics about the event. These events have all occurred around a city. Ultimately I'd like to have a grid over a map that divides the city into zones and then use the model to predict the likelihood of the event occurring within each grid square given a specified day of the week, time of the day, weather etc.
I began by choosing an initial area to focus on (main metro area) and filtered out all the data that was not within that "box". I then used Discretize by Binning to divide that area into zones for both the X and Y coordinate and then merged those attributes into one.
I'm not sure if I am on the correct track or not, but at this point I'm stuck on what to do next?
Could anyone point me in the right direction or provide me with a previous tutorial/example for predicting the location of events?