Apache Spark Use Case Projects: San Francisco Crime Classification

The goal: Predict the category of crimes that occurred in the city by the bay

This task was published on Kaggle Competition. Please read about details on original source.

About the dataset

This dataset contains incidents derived from SFPD Crime Incident Reporting system. The data ranges from 1/1/2003 to 5/13/2015. The training set and test set rotate every week, meaning week 1,3,5,7... belong to test set, week 2,4,6,8 belong to training set.

Data fields:

Dates - timestamp of the crime incident

Category - category of the crime incident (only in train.csv). This is the target variable you are going to predict.

Descript - detailed description of the crime incident (only in train.csv)

DayOfWeek - the day of the week

PdDistrict - name of the Police Department District

Resolution - how the crime incident was resolved (only in train.csv)

Address - the approximate street address of the crime incident

X - Longitude

Y - Latitude

Possible Solution

This use case could be solved by applying Apache Spark MLlib RandomForestClassifier algorithm.