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 8):
A non-transitory computer-readable medium storing instructions, the instructions comprising:\n one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to:\n identify, from received data, training data and scoring data for a model; \n train the model with the training data to generate a plurality of trained models; \n process the plurality of trained models, with the scoring data, to generate scores for the plurality of trained models; \n select a trained model, from the plurality of trained models, based on model metrics and the scores; \n process a training sample, with the trained model, to generate first results,\n the training sample having been created based on the training data and production data associated with a production environment in which the trained model is to be utilized; \n \n process a production sample, with the trained model, to generate second results,\n the production sample having been created based on the production data and the training sample; \n \n validate the trained model for use in the production environment based on the first results and the second results match; and \n provide the trained model to be used in the production environment based on validating the trained model.

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): 0.4012522117240426
- 35 USC 102 Novelty (BERT): 0.4883570788708598
- Combined Prediction Score: 0.4099626984387243
- Mean Citation Score: 216.481962
- Max Citation Score: 222.94238
- Similarity Product: 159.13450639943605

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