AUTOMATICALLY DETERMINING A CURRENT VALUE FOR A HOME
First Claim
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1. A method for valuing a distinguished home located in a distinguished geographic area, comprising:
- retrieving home sales data for the distinguished geographic area, the home sales data comprising a plurality of entries each indicating, for a home located in the distinguished geographic area that was recently sold, a selling price, and, for each of a plurality of attributes, the value of the attribute for the home;
creating a plurality of classification trees for the distinguished geographic area;
for each of the classification trees;
randomly selecting a proper subset of the plurality of entries;
randomly selecting a proper subset of the plurality of attributes;
for each of the selected attributes, determining the full range of values of the selected attribute among the selected entries;
establishing a root node representing all of the selected entries and the full range of values of each of the selected attributes;
for each node of the tree;
determining the information gain borne by each possible split of each of the ranges of the selected attributes represented by the node to the selling prices of the entries represented by the node;
when the greatest information gain of a possible split exceeds the information gain of the node;
performing the possible split having the greatest information gain to divide the range into two subranges at a point in the attribute range that produces the largest variance between an average selling price for the subranges to an average selling price for the range;
for each of the two subranges, establishing a child of the node representing the subrange and the homes represented by the node whose attribute values fall into the subrange;
when the greatest information gain of a possible split does not exceed the information gain of the node, identifying the node as a leaf node and calculating a mean selling price for the homes represented by the node;
for each of a proper subset of the plurality of entries that excludes the selected entries;
identifying a leaf node of the classification tree representing attribute ranges containing the entry'"'"'s attributes;
comparing the price of the identified leaf node to the selling price of the entry;
scoring the classification tree based on the extent to which the prices of the identified leaf nodes differed from the corresponding selling prices;
receiving attributes of the distinguished home;
for each of the classification trees, identifying a leaf node of the classification tree representing attribute ranges containing the distinguished home'"'"'s attributes;
determining an average of the price of the identified leaf node in each of the trees that is weighted by the tree'"'"'s score; and
reporting the determined average as the value of the distinguished home.
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Abstract
A facility for valuing a distinguished home located in a distinguished geographic area is described. The facility receives home attributes for the distinguished home. The facility obtains valuation for the distinguished home by applying to the received home attributes evaluation model for homes in the distinguished geographic area that has been trained using selling price and home attribute data from homes recently sold in the distinguished geographic area. The facility reports the obtained valuation for the distinguished home.
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Citations
29 Claims
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1. A method for valuing a distinguished home located in a distinguished geographic area, comprising:
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retrieving home sales data for the distinguished geographic area, the home sales data comprising a plurality of entries each indicating, for a home located in the distinguished geographic area that was recently sold, a selling price, and, for each of a plurality of attributes, the value of the attribute for the home; creating a plurality of classification trees for the distinguished geographic area; for each of the classification trees; randomly selecting a proper subset of the plurality of entries; randomly selecting a proper subset of the plurality of attributes; for each of the selected attributes, determining the full range of values of the selected attribute among the selected entries; establishing a root node representing all of the selected entries and the full range of values of each of the selected attributes; for each node of the tree; determining the information gain borne by each possible split of each of the ranges of the selected attributes represented by the node to the selling prices of the entries represented by the node; when the greatest information gain of a possible split exceeds the information gain of the node; performing the possible split having the greatest information gain to divide the range into two subranges at a point in the attribute range that produces the largest variance between an average selling price for the subranges to an average selling price for the range; for each of the two subranges, establishing a child of the node representing the subrange and the homes represented by the node whose attribute values fall into the subrange; when the greatest information gain of a possible split does not exceed the information gain of the node, identifying the node as a leaf node and calculating a mean selling price for the homes represented by the node; for each of a proper subset of the plurality of entries that excludes the selected entries; identifying a leaf node of the classification tree representing attribute ranges containing the entry'"'"'s attributes; comparing the price of the identified leaf node to the selling price of the entry; scoring the classification tree based on the extent to which the prices of the identified leaf nodes differed from the corresponding selling prices; receiving attributes of the distinguished home; for each of the classification trees, identifying a leaf node of the classification tree representing attribute ranges containing the distinguished home'"'"'s attributes; determining an average of the price of the identified leaf node in each of the trees that is weighted by the tree'"'"'s score; and reporting the determined average as the value of the distinguished home.
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2. A computer-readable medium whose contents cause a computing system to perform a method for valuing a distinguished home located in a distinguished geographic area, the method comprising:
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receiving home attributes for the distinguished home; obtaining a valuation for the distinguished home by applying to the received home attributes a classification tree-based valuation model for homes in the distinguished geographic area trained using selling price and home attribute data from homes recently sold in the distinguished geographic area; and reporting the obtained valuation for the distinguished home. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method in a computing system for establishing a valuation model for homes in a distinguished geographic area, comprising:
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identifying sales information for homes in the distinguished geographic area sold after a distinguished past date, the sales information including home attributes and selling price for each home; initializing a valuation model that is a forest of classification trees; and training the initialized valuation model with the identified sales information for at least a portion of the homes in the distinguished geographic area sold after the distinguished past date, such that the trained valuation model values each of these homes at or near its selling price, wherein each of classification trees is weighted based upon a level of success of the classification tree in valuing homes in the distinguished geographic area that were recently sold other than those used to train the valuation model. - View Dependent Claims (15, 18, 19, 20, 21, 22, 23, 24, 25)
and wherein homes are identified whose difference between selling price from second most recent sale to valuation obtained by applying the second valuation model lies outside a second predetermined percentage range.
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21. The method of claim 14, further comprising:
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identifying a home in the distinguished geographic area sold after the distinguished past date having an attribute for which no value is available; and in response to the identifying, imputing a value of the attribute for the identified home.
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22. The method of claim 19, further comprising choosing as the imputed attribute value the median value of the attribute among homes in the distinguished geographic area sold after the distinguished date.
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23. The method of claim 19, further comprising choosing as the imputed attribute value the mode value of the attribute among homes in the distinguished geographic area sold after the distinguished date.
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24. The method of claim 14, further comprising:
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identifying a home in the distinguished geographic area sold after the distinguished past date for which no selling price is available; and in response to the identifying, imputing a selling price for the identified home.
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25. The method of claim 24, further comprising:
choosing as the imputed selling price the product of a loan amount and an estimated regional home-to-value ratio.
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16-17. -17. (canceled)
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26. One or more computer memories collectively containing a forest of classification trees usable to value homes in a distinguished geographic area, each of the trees of the forest classifying a random subset of homes and their recent selling prices based on values of a random subset of known home attributes,
such that the forest may be used to value a home in the distinguished geographic area based upon its home attributes, wherein associated with each tree of the forest is a weight indicating the likely level of accuracy of values produced by the tree relative to the other trees.
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27. (canceled)
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28. A method of valuing a distinguished home located in a distinguished geographic area, comprising:
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receiving home attributed for the distinguished home; obtaining a valuation for the distinguished home by applying to the received home attributes a classification tree-based valuation model for homes in the distinguished geographic area trained using selling price and home attribute data from homes recently sold in the distinguished geographic area; and reporting the obtained valuation for the distinguished home.
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29. A computing system for establishing a valuation model for homes in a distinguished geographic area, comprising:
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an identifying unit configured to identify sales information for homes in the distinguished geographic area sold after a distinguished past date, the sales information including home attributes and selling price for each home; an initializing unit configured to initialize a valuation model that is a forest of classification trees; and a training unit configured to train the initialized valuation model with the identified sales information for at least a portion of the homes in the distinguished geographic area sold after the distinguished past date, such that the trained valuation model values each of these homes at or near its selling price, wherein each of classification trees is weighted based upon a level of success of the classification tree in valuing home in the distinguished geographic area that were recently sold other than those used to train the valuation model.
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Specification