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 1):
A system for tuning a machine learning model for improved effectiveness including accuracy and computational performance, the system comprising:\n an intelligent machine learning tuning platform that is hosted on a distributed networked system comprising:\n a cluster of distinct machine learning tuning sources that perform distinct tuning operations of hyperparameters of machine learning models; \n a plurality of queue worker machines that selectively operate one or more of the cluster of distinct tuning sources based on a receipt of a tuning work request, wherein the plurality of queue worker machines includes a plurality of distinct queue worker machines that operate asynchronously to perform disparate tuning operations using one or more of the cluster of distinct machine learning tuning sources; \n a shared work queue that is accessible by each of the plurality of distinct queue worker machines, wherein the shared work queue comprises an asynchronous queue that enable asynchronous tuning operations by the plurality of queue worker machines; \n a platform database comprising a central repository that collects tuning data generated during tuning trials of the hyperparameters of the machine learning model.

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): 0.349644668024912
- 35 USC 102 Novelty (BERT): 0.481175182008874
- Combined Prediction Score: 0.3627977194233082
- Mean Citation Score: 165.13183999999995
- Max Citation Score: 202.97345
- Similarity Product: 148.85294651902618

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

Dataset: test