PATENT CLAIM ANALYSIS

Application Number: 15893572
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["714", "057000"]

Abstract:
Examples for detecting anomalies in a dataset are provided herein. A decision tree is trained using the data set and partitions of the data set produced by the trained decision tree are identified. Further, subsets of data based at least on the partitions of the data set are identified and z-scores are computed for the subsets of data. Based at least on the subsets of data, a subset of data with a highest z-score is identified as an anomalous subset of data, and the anomalous subset of data is provided for display.

Claim (Index 19):
The one or more computer-readable storage media of  claim 17 , wherein each of the subsets of data correspond to a particular terminal node of a plurality of terminal nodes generated by the trained decision tree, and wherein the data set comprises a plurality of columns of data and a plurality of rows of data, and wherein each of the plurality of terminal nodes indicate which rows of the plurality of rows are in a particular subset of data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 2.25
- Patent Class: 714.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14687848', '15069797', '12940432', '11825527', '15806265']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.288752053941663
- 35 USC 102 Novelty (BERT): 0.480178314543787
- Combined Prediction Score: 0.3078946800018754
- Mean Citation Score: 144.725984
- Max Citation Score: 156.90282
- Similarity Product: 103.9025957886672

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