Automatically determining a current value for a real estate property, such as a home, that is tailored to input from a human user, such as its owner

A method, performed by a computing system having one or more processors, the method comprising:

• constructing, with at least one processor of the one or more processors, a model at least in part by,
• identifying attributes of a first property from among a plurality of properties recently sold in a geographic region and a selling price of the first property,
• creating a first tuple made up of values for the identified attributes of the first property and the selling price of the first property,
• identifying attributes of a second property from among the plurality of properties recently sold in the geographic region and a selling price of the second property,
• creating a second tuple made up of values for the identified attributes of the second property and the selling price of the second property,
• identifying attributes of a third property from among the plurality of properties recently sold in the geographic region and a selling price of the third property,
• creating a third tuple made up of values for the identified attributes of the third property and the selling price of the third property, and
• constructing a plurality of classification trees, wherein constructing a first classification tree of the plurality of classification trees comprises:
• randomly selecting a fraction of the plurality of properties recently sold in the geographic region,
• creating a root node for the first classification tree of the plurality of classification trees, the root node created for the first classification tree of the plurality of classification trees representing the randomly selected fraction of the plurality of properties recently sold in the geographic region and a range of values for at least one attribute,
• determining that the root node created for the first classification tree of the plurality of classification trees should be split,
• in response to determining that the root node created for the first classification tree of the plurality of classification trees should be split:
• creating a first child node for the root node created for the first classification tree of the plurality of classification trees and a second child node for the root node created for the first classification tree of the plurality of classification trees;
• and
• generating, using the constructed model, an automatic valuation of a fourth property other than the plurality of properties recently sold in the geographic region, using only information about the fourth property originated by a public source, at least in part by traversing at least one of the plurality of classification trees.

A non-transitory computer-readable medium storing contents that cause a computing system having a memory and at least one processor to:

• construct a model at least in part by,
• identifying attributes of a first property from among a plurality of properties recently sold in a geographic region and a selling price of the first property,
• creating a first tuple made up of values for the identified attributes of the first property and the selling price of the first property,
• identifying attributes of a second property from among the plurality of properties recently sold in the geographic region and a selling price of the second property,
• creating a second tuple made up of values for the identified attributes of the second property and the selling price of the second property,
• identifying attributes of a third property from among the plurality of properties recently sold in the geographic region and a selling price of the third property,
• creating a third tuple made up of values for the identified attributes of the third property and the selling price of the third property, and
• constructing a plurality of classification trees, wherein constructing a first classification tree of the plurality of classification trees comprises:
• randomly selecting a fraction of the plurality of properties recently sold in the geographic region,
• creating a root node for the first classification tree of the plurality of classification trees, the root node created for the first classification tree of the plurality of classification trees representing the randomly selected fraction of the plurality of properties recently sold in the geographic region and a range of values for at least one attribute,
• determining that the root node created for the first classification tree of the plurality of classification trees should be split,
• in response to determining that the root node created for the first classification tree of the plurality of classification trees should be split:
• creating a first child node for the root node created for the first classification tree of the plurality of classification trees and a second child node for the root node created for the first classification tree of the plurality of classification trees;
• and
• generate, using the constructed model, an automatic valuation of a fourth property other than the plurality of properties recently sold in the geographic region, using only information about the fourth property originated by a public source, at least in part by traversing at least one of the plurality of classification trees.