Machine Learning - Typology
Classifying Architectural Typologies with Unsupervised Learning
Independent — 2017



Coming soon...

This research, currently in progress, applies unsupervised learning techniques to the classification of building typology. Using python code and physical data from a New York City’s Department of City Planning dataset, this algorithm takes an address as an input and outputs a prediction of building type (i.e. single family residence, warehouse, cathedral).

Applied techniques include data exploration, benchmarking, data preprocessing, feature transformation, Gaussian mixture
model clustering, and k-means clustering.





Copyright © 2017 Jim Peraino.
All rights reserved.