PATENT CLAIM ANALYSIS

Application Number: 16055336
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["706", "012000"]

Abstract:
A computing device determines a bandwidth parameter value for outlier detection or data classification. A mean pairwise distance value is computed between observation vectors. A tolerance value is computed based on a number of observation vectors. A scaling factor value is computed based on a number of observation vectors and the tolerance value. A Gaussian bandwidth parameter value is computed using the mean pairwise distance value and the scaling factor value. An optimal value of an objective function is computed that includes a Gaussian kernel function that uses the computed Gaussian bandwidth parameter value. The objective function defines a support vector data description model using the observation vectors to define a set of support vectors. The Gaussian bandwidth parameter value and the set of support vectors are output for determining if a new observation vector is an outlier or for classifying the new observation vector.

Claim (Index 29):
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 compute a mean pairwise distance value between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables; \n compute a tolerance value based on a number of the plurality of observation vectors; \n compute a scaling factor value based on the number of the plurality of observation vectors and the computed tolerance value; \n compute a Gaussian bandwidth parameter value using the computed mean pairwise distance value and the computed scaling factor value; \n compute an optimal value of an objective function that includes a Gaussian kernel function that uses the computed Gaussian bandwidth parameter value, wherein the objective function defines a support vector data description (SVDD) model using the plurality of observation vectors to define a set of support vectors; and \n output the computed Gaussian bandwidth parameter value and the defined a set of support vectors for determining if a new observation vector is an outlier or for classifying the new observation vector.

Metadata:
- Claim Count in Document: 81.0
- Percentile: 96.0
- Lexical Diversity: 2.63793
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15583067', '15185277', '15390236', '15096552', '15335530']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4517026363909769
- 35 USC 102 Novelty (BERT): 0.5447119754983193
- Combined Prediction Score: 0.4610035703017111
- Mean Citation Score: 387.070814
- Max Citation Score: 424.97754
- Similarity Product: 322.99711150287146

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