Machine learning system

Abstract

Methods, systems, and computer program products are included for providing a predicted outcome to a user interface. An exemplary method includes receiving, from a user interface, a plurality of identifiers that identify objects. At the user interface, a target success function is selected corresponding to the plurality of identifiers. The target success function is mapped to at least one attribute of one or more attributes of the objects. The at least one attribute of the objects and one or more other attributes are queried. Data values are retrieved corresponding to the queried at least one attribute and the one or more other attributes. Based on the data values, an outcome of the target success function is predicted. The predicted outcome is provided to the user interface.

What is claimed is: 
     
         1 . A system comprising:
 a non-transitory memory; and   one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising:
 receiving, from a user interface, a plurality of identifiers that identify objects of a first type; 
 receiving, from the user interface, a selection of a target success function corresponding to the plurality of identifiers; 
 mapping the target success function to at least one attribute of one or more attributes of the objects; 
 querying the at least one attribute of the objects and one or more other attributes; 
 retrieving data values corresponding to the queried at least one attribute and the one or more other attributes; 
 predicting, based on the data values, an outcome of the target success function; and 
 providing, to the user interface, the predicted outcome. 
   
     
     
         2 . The system of  claim 1 , wherein the mapping comprises a stored association between the target success function and the at least one attribute. 
     
     
         3 . The system of  claim 1 , wherein the mapping comprises a user selection of the at least one attribute corresponding to the target success function. 
     
     
         4 . The system of  claim 1 , wherein the data values corresponding to the queried at least one attribute include a first data value that is a dependent variable used for the predicting, and wherein the data values corresponding to the queried one or more other attributes include a second data value that is an independent variable used for the predicting. 
     
     
         5 . The system of  claim 1 , the operations further comprising:
 providing, to the user interface, a confidence interval corresponding to the predicted outcome.   
     
     
         6 . The system of  claim 1 , wherein receiving the plurality of identifiers comprises receiving a selection of a plurality of objects from a data store. 
     
     
         7 . The system of  claim 1 , wherein the objects of the same type comprise a plurality of objects, and wherein each object of the plurality of objects includes a same set of attributes. 
     
     
         8 . A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:
 receiving, from a user interface, a plurality of identifiers that identify objects of a first type;   receiving, from the user interface, a selection of a target success function corresponding to the plurality of identifiers;   mapping the target success function to at least one attribute of one or more attributes of the objects;   querying the at least one attribute of the objects and one or more other attributes;   retrieving data values corresponding to the queried at least one attribute and the one or more other attributes;   predicting, based on the data values, an outcome of the target success function; and   providing, to the user interface, the predicted outcome.   
     
     
         9 . The non-transitory machine-readable medium of  claim 8 , wherein the mapping comprises a stored association between the target success function and the at least one attribute. 
     
     
         10 . The non-transitory machine-readable medium of  claim 8 , wherein the mapping comprises a user selection of the at least one attribute corresponding to the target success function. 
     
     
         11 . The non-transitory machine-readable medium of  claim 8 , wherein the data values corresponding to the queried at least one attribute include a first data value that is a dependent variable used for the predicting, and wherein the data values corresponding to the queried one or more other attributes include a second data value that is an independent variable used for the predicting. 
     
     
         12 . The non-transitory machine-readable medium of  claim 8 , the operations further comprising:
 providing, to the user interface, a confidence interval corresponding to the predicted outcome.   
     
     
         13 . The non-transitory machine-readable medium of  claim 8 , wherein receiving the plurality of identifiers comprises receiving a selection of a plurality of objects from a data store. 
     
     
         14 . The non-transitory machine-readable medium of  claim 8 , wherein the objects of the same type comprise a plurality of objects, and wherein each object of the plurality of objects includes a same set of attributes. 
     
     
         15 . A method comprising:
 receiving, by a machine learning component from a user interface, a plurality of identifiers that identify objects of a same type;   receiving, by the machine learning component from the user interface, a selection of a target success function corresponding to the plurality of identifiers;   mapping, by the machine learning component, the target success function to at least one attribute of one or more attributes of the objects;   querying, by the machine learning component the at least one attribute of the objects and one or more other attributes;   retrieving, by the machine learning component data values corresponding to the queried at least one attribute and the one or more other attributes;   predicting, by the machine learning component based on the data values, an outcome of the target success function; and   providing, by the machine learning component to the user interface, the predicted outcome.   
     
     
         16 . The method of  claim 15 , wherein the mapping comprises a stored association between the target success function and the at least one attribute. 
     
     
         17 . The method of  claim 15 , wherein the data values corresponding to the queried at least one attribute include a first data value that is a dependent variable used for the predicting, and wherein the data values corresponding to the queried one or more other attributes include a second data value that is an independent variable used for the predicting. 
     
     
         18 . The method of  claim 15 , further comprising:
 providing, by the machine learning component to the user interface, a confidence interval corresponding to the predicted outcome.   
     
     
         19 . The method of  claim 15 , wherein receiving the plurality of identifiers comprises receiving a selection of a plurality of objects from a data store. 
     
     
         20 . The method of  claim 15 , wherein the objects of the same type comprise a plurality of objects, and wherein each object of the plurality of objects includes a same set of attributes.