Machine Learning - Typology
Classifying Architectural Typologies with Unsupervised Learning
Independent — 2017
Classifying Architectural Typologies with Unsupervised Learning
Independent — 2017
In Progress...
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, analyzes the site’s dimensions and proportions, 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.
Github
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, analyzes the site’s dimensions and proportions, 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.
Github
