In Sopra Steria Analytics Sweden's very first blog, 24-hour predictions of PM10 levels in urban environments, I applied Random Forest methods to predict levels of particles at street level in Stockholm. These methods are widely used to either predict values of measurements given features in a dataset (regression) or to segment objects or populations (classification).... Continue Reading →