PATENT CLAIM ANALYSIS

Application Number: 15941552
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-08
Patent Classification: ["370", "252000"]

Abstract:
A recursive algorithm may be applied to group cells in a service network into a small number of clusters. For each of the clusters, different regression algorithms may be evaluated, and a regression algorithm generating a smallest error is selected. A total error for the clusters may be identified based on the errors from the selected regression algorithms and from degrees of separation associated with the cluster. If the total error is greater than a threshold value, the cells may be grouped into a larger number of clusters and the new clusters may be re-evaluated. A key performance indicator (KPI) may be estimated for a cell based on a regression algorithm selected for the cluster associated with the cell. A resources may be allocated to the cell based on the KPI value.

Claim (Index 2):
The method of  claim 1 , wherein the group of regression algorithms includes at least two of:\n a generalized additive model (GAM), a gradient boost method (GBM), a neural network method, or multivariate adaptive regression splines (MARS) method.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.23438
- Patent Class: 370.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15087129', '14975116', '14273433', '14248056', '15373177']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5583478358824846
- 35 USC 102 Novelty (BERT): 0.498031833448034
- Combined Prediction Score: 0.5523162356390395
- Mean Citation Score: 167.14679699999996
- Max Citation Score: 296.3735
- Similarity Product: 291.8706840364038

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