PATENT CLAIM ANALYSIS

Application Number: 16172430
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2020-01
Patent Classification: ["706", "015000"]

Abstract:
A model optimizer is disclosed for managing training of models with automatic hyperparameter tuning. The model optimizer can perform a process including multiple steps. The steps can include receiving a model generation request, retrieving from a model storage a stored model and a stored hyperparameter value for the stored model, and provisioning computing resources with the stored model according to the stored hyperparameter value to generate a first trained model. The steps can further include provisioning the computing resources with the stored model according to a new hyperparameter value to generate a second trained model, determining a satisfaction of a termination condition, storing the second trained model and the new hyperparameter value in the model storage, and providing the second trained model in response to the model generation request.

Claim (Index 14):
The system of  claim 1 , wherein the performance metric depends on at least one of a statistical correlation score, a data similarity score, or a data quality score.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 97.0
- Lexical Diversity: 2.55556
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16172344', '16172508', '16151385', '15822462', '16059241']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4436161404435624
- 35 USC 102 Novelty (BERT): 0.520936675327421
- Combined Prediction Score: 0.4513481939319482
- Mean Citation Score: 302.266202
- Max Citation Score: 349.2498
- Similarity Product: 329.24341695127487

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

Dataset: test