IP Library Patent Application 14314811
Patent Application
App. No. 14/314,811

MODEL COMPILATION FOR FEATURE SELECTION IN STATISTICAL MODELS

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Quick Facts
Patent No.
US None
App. No.
14/314,811
Abstract

The disclosed embodiments provide a system and method for processing data. The system includes a model compiler that obtains a first configuration for a statistical model. The first configuration may include one or more compilation parameters associated with feature selection in the statistical model. Next, the model compiler uses the compilation parameter(s) and a first set of input features for the first configuration to generate a first feature subset for use with the statistical model and include the first feature subset in a first compiled form of the first configuration. The system also includes an execution engine that uses the first compiled form to execute the statistical model.

Claims (69)

1 . A computer-implemented method for processing data, comprising:

obtaining a first configuration for a statistical model, wherein the first configuration comprises one or more compilation parameters associated with feature selection in the statistical model;

using the one or more compilation parameters and a first set of input features for the first configuration to generate a first feature subset for use with the statistical model; and

including the first feature subset in a first compiled form of the first configuration, wherein the first compiled form is used to execute the statistical model.

2 . The computer-implemented method of claim 1 , further comprising:

providing the first feature subset as a second set of input features for a second configuration for the statistical model;

using one or more additional compilation parameters from the second configuration and the second set of input features to generate a second feature subset for use with the statistical model; and

including the second feature subset in a second compiled form of the second configuration, wherein the second compiled form is further used to execute the statistical model.

3 . The computer-implemented method of claim 1 , wherein the first configuration is associated with at least one of a feature source, a transformer, and an assembler.

4 . The computer-implemented method of claim 3 ,

wherein the transformer is a subset transformer that generates the first feature subset as a subset of the first set of input features, and

wherein the one or more compilation parameters comprise at least one of a minimum support, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

5 . The computer-implemented method of claim 3 ,

wherein the transformer is a bucketizing transformer that transforms a numeric input feature into a set of binary numeric features, and

wherein the one or more compilation parameters comprise an input feature and a number of buckets.

6 . The computer-implemented method of claim 3 ,

wherein the transformer is a disjunction transformer that performs a logical disjunction of one or more sets of binary input features, and

wherein the one or more compilation parameters comprise the one or more sets of binary features.

7 . The computer-implemented method of claim 3 ,

wherein the transformer is an interaction transformer that calculates an outer product of a first subset of input features from the first set of input features and a second subset of input features from the first set of input features, and

wherein the one or more compilation parameters comprise at least one of the first set of features, the second set of features, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

8 . The computer-implemented method of claim 3 ,

wherein the transformer is a summation transformer that sums a set of values for an input feature over a range, and

wherein the one or more compilation parameters comprise the input feature and the range.

9 . The computer-implemented method of claim 1 , wherein using the one or more compilation parameters and the first set of input features to generate the first feature subset comprises:

obtaining an index map associated with the first set of input features; and

using the index map to match a feature name pattern from the one or more compilation parameters to one or more feature indexes in the first set of input features; and

including the one or more feature indexes in the first feature subset.

10 . A system for processing data, comprising:

a model compiler configured to:

obtain a first configuration for a statistical model, wherein the first configuration comprises one or more compilation parameters associated with feature selection in the statistical model;

use the one or more compilation parameters and a first set of input features for the first configuration to generate a first feature subset for use with the statistical model; and

include the first feature subset in a first compiled form of the first configuration; and

an execution engine configured to use the first compiled form to execute the statistical model.

11 . The system of claim 10 ,

wherein the model compiler is further configured to:

use the first feature subset as a second set of input features for a second configuration for the statistical model;

use one or more additional compilation parameters from the second configuration and the second set of input features to generate a second feature subset for use with the statistical model; and

include the second feature subset in a second compiled form of the second configuration, and

wherein the execution engine is further configured to use the second compiled form to execute the statistical model.

12 . The system of claim 10 ,

wherein the first configuration is associated with a subset transformer that generates the first feature subset as a subset of the first set of input features, and

wherein the one or more compilation parameters comprise at least one of a minimum support, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

13 . The system of claim 10 ,

wherein the first configuration is associated with a disjunction transformer that performs a logical disjunction of one or more sets of binary input features, and

wherein the one or more compilation parameters comprise the one or more sets of binary features.

14 . The system of claim 10 ,

wherein the first configuration is associated with an interaction transformer that calculates an outer product of a first subset of input features from the first set of input features and a second subset of input features from the first set of input features, and

wherein the one or more compilation parameters comprise at least one of the first set of features, the second set of features, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

15 . The system of claim 10 ,

wherein the first configuration is associated with a summation transformer that sums a set of values for an input feature over a range, and

wherein the one or more compilation parameters comprise the input feature and the range.

16 . A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for processing data, the method comprising:

obtaining a first configuration for a statistical model, wherein the first configuration comprises one or more compilation parameters associated with feature selection in the statistical model;

using the one or more compilation parameters and a first set of input features for the first configuration to generate a first feature subset for use with the statistical model; and

including the first feature subset in a first compiled form of the first configuration, wherein the first compiled form is used to execute the statistical model.

17 . The non-transitory computer-readable storage medium of claim 16 , the method further comprising:

providing the first feature subset as a second set of input features for a second configuration for the statistical model;

using one or more additional compilation parameters from the second configuration and the second set of input features to generate a second feature subset for use with the statistical model; and

including the second feature subset in a second compiled form of the second configuration, wherein the second compiled form is further used to execute the statistical model.

18 . The non-transitory computer-readable storage medium of claim 16 ,

wherein the first configuration is associated with a subset transformer that generates the first feature subset as a subset of the first set of input features, and

wherein the one or more compilation parameters comprise at least one of a minimum support, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

19 . The non-transitory computer-readable storage medium of claim 16 ,

wherein the first configuration is associated with an interaction transformer that calculates an outer product of a first subset of input features from the first set of input features and a second subset of input features from the first set of input features, and

wherein the one or more compilation parameters comprise at least one of the first set of features, the second set of features, a minimum support fraction, a minimum mutual information, a maximum number of features, and a comparator associated with sorting the first set of input features.

20 . The non-transitory computer-readable storage medium of claim 16 ,

wherein the first configuration is associated with a summation transformer that sums a set of values for an input feature over a range, and

wherein the one or more compilation parameters comprise the input feature and the range.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 1, 2017
From: LINKEDIN CORPORATION
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 044746/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 24, 2014
From: XIN, DORIS S.; TRAUPMAN, JONATHAN D.; MENG, XIANGRUI; OGILVIE, PAUL T.
To: LINKEDIN CORPORATION
Reel/Frame 033385/0718 →