PATENT CLAIM ANALYSIS

Application Number: 15750363
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-01
Patent Classification: ["717", "124000"]

Abstract:
Certain aspects involve building and debugging models for generating source code executed on data-processing platforms. A target data-processing platform is identified that requires bin ranges for modeling coefficients and reason codes for input attributes. A processor outputs source code, which is generated from a modeling code, in a programming language used by the target data-processing platform.

Claim (Index 16):
The method of  claim 9 , wherein the modeling code comprises a specification of the model in a predictive model interchange format and the executable source code comprises source code to be compiled by the data-processing platform, wherein the user interface further comprises additional interface elements for:\n (i) identifying a mapping of the one or more input attributes to one or more production attributes from the data-processing platform, (ii) identifying one or more transformations of one or more values of the one or more production attributes into one or more values compliant with the electronic data-processing model, (iii) uploading, to a non-transitory computer-readable medium accessible to the model integration tool, first PMML code implementing a first decision tree and second PMML code implementing a second decision tree, (iv) indicating an input attribute whose value controls a selection of the first decision tree or the second decision tree, and (v) uploading, to the non-transitory computer-readable medium, an audit file having the expected analytical output and the expected reason code, wherein the modeling code implements the mapping, the one or more transformations, the first decision tree, the second decision tree, and segmentation logic that selects the first decision tree based on the input attribute having a first value and selects the second decision tree based on the input attribute having a second value, wherein verifying that the test analytical output matches the expected analytical output and the test reason code matches the expected reason code comprises accessing the audit file from the non-transitory computer-readable medium and comparing the expected analytical output and the expected reason code stored in the audit file with the test analytical output and the test reason code, wherein the method further comprises, prior to verifying that the test analytical output matches the expected analytical output and the test reason code matches the expected reason code:\n performing, with the model integration tool, an additional test of the electronic data-processing model using the modeling code, \n determining, by the model integration tool, that the additional test results in an additional test analytical output that fails to match the expected analytical output or an additional test reason code that fails to match the expected reason code, and \n updating, with the model integration tool, the modeling code subsequent to the additional test analytical output failing to match the expected analytical output or the additional test reason code failing to match the expected reason code, \n wherein the modeling code as updated results in the test analytical output and the test reason code matching the expected analytical output and the expected reason code.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 88.0
- Lexical Diversity: 1.38636
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16334190', '10443243', '15388388', '12873434', '10126286']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4024707861425451
- 35 USC 102 Novelty (BERT): 0.5020704990291194
- Combined Prediction Score: 0.4124307574312025
- Mean Citation Score: 172.75708799999995
- Max Citation Score: 209.60889
- Similarity Product: 149.95951812868952

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test