PATENT CLAIM ANALYSIS

Application Number: 16433192
Application Type: Utility
Filing Date: 2019-06
Publication Date: 2019-12
Patent Classification: ["703", "002000"]

Abstract:
A computing device provides distributed estimation of an empirical distribution function. A boundary cumulative distribution function (CDF) value is defined at a start of each region of a plurality of regions. An accuracy value is defined for each region. (a) First equal proportion bins are computed for a first sample of a first marginal variable using the defined boundary CDF value for each region. (b) Second equal proportion bins are computed for the first sample of the first marginal variable within each region based on the defined accuracy value for each region. (c) The computed second equal proportion bins are added as an empirical distribution function (EDF) for the first marginal variable. (d) (a) to (c) are repeated for each remaining sample of the first marginal variable. (e) (a) to (d) are repeated with each remaining marginal variable of a plurality of marginal variables as the first marginal variable.

Claim (Index 19):
A computing device comprising:\n a processor; and a non-transitory computer-readable medium operably coupled to the processor, the computer-readable medium having computer-readable instructions stored thereon that, when executed by the processor, cause the computing device to\n define a boundary cumulative distribution function (CDF) value at a start of each region of a plurality of regions; \n define an accuracy value for each region of the plurality of regions; \n (a) compute first equal proportion bins for a first sample of a first marginal variable using the defined boundary CDF value for each region; \n (b) compute second equal proportion bins for the first sample of the first marginal variable within each region based on the defined accuracy value for each region; \n (c) add the computed second equal proportion bins to an empirical distribution function (EDF) for the first marginal variable; \n (d) repeat (a) to (c) for each remaining sample of the first marginal variable; \n (e) repeat (a) to (d) with each remaining marginal variable of a plurality of marginal variables as the first marginal variable; and \n (f) output the EDF computed for each marginal variable of the plurality of marginal variables.

Metadata:
- Claim Count in Document: 53.0
- Percentile: 100.0
- Lexical Diversity: 2.98333
- Patent Class: 703.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16433136', '16161339', '16033851', '15961373', '16140931']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2617007401218202
- 35 USC 102 Novelty (BERT): 0.527467363416355
- Combined Prediction Score: 0.2882774024512737
- Mean Citation Score: 219.618288
- Max Citation Score: 335.3869
- Similarity Product: 247.5334556273103

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

Dataset: test