Federal Home Loan Mortgage Corporation (freddie Mac)

Jianglong Li

Yuang Tang

Fabio Quijada

In an illustrative embodiment, systems and methods include storing, to feature vectors of real estate properties, both property attributes and at least one geospatial feature located within a predetermined distance of the property's location, evaluating, using machine learning (ML) algorithm(s), subsets of properties to identify impactful features having a significant impact on property value for each property subset, and, using an ML model trained for the impactful features of a given property subset, analyze feature data to obtain a) a set of similar properties and/or b) a property valuation for each of one or more real estate properties.

Systems and methods of establishing correlative relationships between geospatial data features in feature vectors representing property locations

In an illustrative embodiment, an automated system engineers customized feature vectors from geospatial information system (GIS) metadata. The system may include computing systems and devices for extracting metadata for GIS features located within a predetermined distance of a property from a GIS map file and storing the extracted GIS features within a feature vector. The system can augment each of the extracted GIS features with amplifying data features extracted from external data sources. The system can calculate a distance between the property and each extracted GIS feature, which establishes a relationship between the property and each GIS feature and associated amplifying data features. Amounts of correlation between each of the extracted GIS features and associated amplifying data features within the feature vector and a market assessment of the property location can be identified using a data model trained with a data set customized to characteristics of the property.

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McLean, VA, United States of America

Jianglong Li