PATENT CLAIM ANALYSIS

Application Number: 16119536
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-05
Patent Classification: ["706", "012000"]

Abstract:
A device identifies training data and scoring data for a model, and removes bias from the training data to generate unbiased training data. The device trains the model with the unbiased training data to generate trained models, and processes the trained models, with the scoring data, to generate scores for the trained models. The device selects a trained model, from the trained models, based on model metrics and the scores, and processes a training sample, with the trained model, to generate first results, wherein the training sample is created based on the unbiased training data and production data. The device processes a production sample, with the trained model, to generate second results, wherein the production sample is created based on the production data and the training sample. The device provides the trained model for use in a production environment based on the first results and the second results.

Claim (Index 19):
The method of  claim 15 , further comprising:\n identifying a portion of the training data; capturing specific production data, of the production data and associated with the portion of the training data, from the production environment; and creating the training sample based on the portion of the training data and the specific production data.

Metadata:
- Claim Count in Document: 8.0
- Percentile: 96.0
- Lexical Diversity: 3.95238
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15961392', '13101048', '15762062', '13014223', '13970791']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3989771716828024
- 35 USC 102 Novelty (BERT): 0.4982426713234231
- Combined Prediction Score: 0.4089037216468645
- Mean Citation Score: 216.481962
- Max Citation Score: 222.94238
- Similarity Product: 140.0875364373076

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

Dataset: test