	US 11,769,181 B2
	Automatically determining a current value for a home
Stanley B. Humphries, Sammamish, WA (US); Dong Xiang, Sammamish, WA (US); Kyusik Chung, Seattle, WA (US); and Jonathan Lee Burstein, Seattle, WA (US)
Assigned to MFTB Holdco. Inc., Seattle, WA (US)
Filed by Zillow, Inc., Seattle, WA (US)
Filed on Dec. 22, 2021, as Appl. No. 17/559,715.
Application 17/559,715 is a division of application No. 16/125,318, filed on Sep. 7, 2018, granted, now 11,244,361.
Application 16/125,318 is a continuation of application No. 14/167,962, filed on Jan. 29, 2014, granted, now 10,074,111, issued on Sep. 11, 2018.
Application 14/167,962 is a continuation of application No. 11/347,000, filed on Feb. 3, 2006, granted, now 8,676,680, issued on Mar. 18, 2014.
Prior Publication US 2022/0114623 A1, Apr. 14, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/02 (2023.01); G06Q 50/16 (2012.01)

CPC G06Q 30/0278 (2013.01) [G06Q 30/02 (2013.01); G06Q 50/16 (2013.01)]

20 Claims

1. A computer-implemented method, in a computing system having a memory and a processor, for generating machine learning models to value homes located in a distinguished geographic area, comprising:

retrieving, by the processor, home sales data for the distinguished geographic area, the home sales data comprising multiple entries, each entry indicating a selling price and a value for one or more home attributes;

creating, by the processor, one or more machine learning classification trees by:

for each distinguished classification tree of the one or more classification trees:

selecting a subset of the multiple entries;

selecting a subset of the one or more home attributes;

for each of the selected home attributes, determining a range of values of the selected attribute among the selected entries;

establishing a root node in the distinguished classification tree representing the range of values of each of the selected attributes; and

for each distinguished node of the tree that has not been identified as a leaf node, determining a greatest information gain resulting from one or more possible splits in the ranges of values represented by the distinguished node;

when the greatest information gain exceeds an information gain identified for the distinguished node, establishing, for each of two subranges corresponding to the split with the greatest information gain, a child node of the distinguished node; and

when the greatest information gain does not exceed the information gain identified for the distinguished node, identifying the distinguished node as a leaf node and calculating a mean selling price for homes represented by the leaf node.