PATENT CLAIM ANALYSIS

Application Number: 15977168
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["706", "012000"]

Abstract:
A system and method includes receiving a tuning work request for tuning an external machine learning model; implementing a plurality of distinct queue worker machines that perform various tuning operations based on the tuning work data of the tuning work request; implementing a plurality of distinct tuning sources that generate values for each of the one or more hyperparameters of the tuning work request; selecting, by one or more queue worker machines of the plurality of distinct queue worker machines, one or more tuning sources of the plurality of distinct tuning sources for tuning the one or more hyperparameters; and using the selected one or more tuning sources to generate one or more suggestions for the one or more hyperparameters, the one or more suggestions comprising values for the one or more hyperparameters of the tuning work request.

Claim (Index 20):
A computer-implemented method for tuning one or more of a machine learning model, a complex system, and a simulation, the computer-implemented method comprising:\n at a remote tuning service, the remote tuning service being hosted on a distributed networked system of hardware computing servers: receiving, via a network, a tuning work request for tuning an external model or an external system, wherein the tuning work request comprises tuning work data that identifies one or more hyperparameters of the external model or the external system for tuning and constraint data comprising one or more tuning operation constraints; implementing a plurality of distinct application programming interface (API) worker machines that perform various tuning operations based on the tuning work data of the tuning work request; implementing a plurality of distinct tuning sources that generate values for each of the one or more hyperparameters of the tuning work request; selecting, by one or more API worker machines of the plurality of distinct API worker machines, one or more tuning sources of the plurality of distinct tuning sources for tuning the one or more hyperparameters; and using the selected one or more tuning sources to generate values for the one or more hyperparameters of the tuning work request.

Metadata:
- Claim Count in Document: 10.0
- Percentile: 93.0
- Lexical Diversity: 2.97959
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15822462', '15377448', '15404052', '15829981', '15956450']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3497937506705296
- 35 USC 102 Novelty (BERT): 0.4805197968818699
- Combined Prediction Score: 0.3628663552916636
- Mean Citation Score: 165.13183999999995
- Max Citation Score: 202.97345
- Similarity Product: 149.86806686254144

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