Abstract: Embodiments are described for transforming data relatively homogeneous data segments for training or otherwise configuring automated modeling systems. For example, a computing system selects, from standardized data, geographic data objects associated with a completed transaction value greater than the threshold number. The computing system clusters these geographic data objects and combines completed transactions associated with the selected geographic data objects into segments. The computing system performs a similarity analysis for pairs of the geographic data objects by comparing numerically valued attributes of the geographic data objects. The computing system also selects, from the standardized data, remaining completed transactions that are not grouped into segments and combines, based on the similarity analysis and the threshold number, these property transactions into segments such that each completed transaction has been assigned to one or more of the relatively homogeneous segments.

Abstract: Embodiments are described for transforming data relatively homogeneous data segments for training or otherwise configuring automated modeling systems. For example, a computing system selects, from standardized data, geographic data objects associated with a completed transaction value greater than the threshold number. The computing system clusters these geographic data objects and combines completed transactions associated with the selected geographic data objects into segments. The computing system performs a similarity analysis for pairs of the geographic data objects by comparing numerically valued attributes of the geographic data objects. The computing system also selects, from the standardized data, remaining completed transactions that are not grouped into segments and combines, based on the similarity analysis and the threshold number, these property transactions into segments such that each completed transaction has been assigned to one or more of the relatively homogeneous segments.

Abstract: Systems and methods for generating segments of real property transactions by clustering base geographic units are provided. According to one embodiment, information regarding real property transactions is received, each transactions corresponds to a base geographic unit based on a physical location of a real property associated with the transaction at issue. For each value of a clustering function represented within the real property transactions, relatively homogeneous segments of transactions are built by aggregating transactions of the base geographic units into clusters based on a predetermined similarity function evaluating corresponding numerically valued attributes associated with the base geographic units until each segment has a sufficient number of transactions to provide desired accuracy, reliability or usefulness in the context of desired numerical modeling or analysis and all real property transactions have been assigned to a segment.