This project is to identify potential fraud records New York property using unsupervised methods.
The dataset for this project is about the property information such as "lot frontage in feet", "block number", and etc.. We used PCA to reduce dimensionality, performed heuristic distance calculation and auto-encoder algorithm to group the sample records and identify the abnormal record, and concluded commonality for the potential fraud records.