- New York NY, US Yue Xiao - Stanford CA, US Chi Zhang - Catsonville MD, US
Assignee:
CA, INC. - New York NY
International Classification:
G06F 17/30 G06F 21/55 G06F 21/56
Abstract:
A big data processing system includes a features permutations testing function that separates out from among a set of identified compound features, those compound feature permutations that have better capabilities for distinguishing between anomalies observed in respective multi-dimensional feature spaces having as their axes the features of the identified compound features.
Identification Of Distinguishable Anomalies Extracted From Real Time Data Streams
- New York NY, US Jin Zhang - Palo Alto CA, US Lan Xu - Stanford CA, US Chi Zhang - Catsonville MD, US Yue Xiao - Stanford CA, US
Assignee:
CA, INC. - New York NY
International Classification:
G06F 11/07 G06F 17/30
Abstract:
A big data processing system includes a workload trimming function that separates out from among a set of identified anomalies, those that are clearly outliers, rather than ones residing within clusters of anomalies as mapped within an anomalies distribution space. The outlier anomalies are not subjected to a computationally-intensive anomalies aggregating process and thus, processing resources are conserved.
Identification Of Distinguishing Compound Features Extracted From Real Time Data Streams
- New York NY, US Yue Xiao - Stanford CA, US Chi Zhang - Catsonville MD, US
Assignee:
CA, INC. - New York NY
International Classification:
G06F 17/30 G06F 21/56
Abstract:
A big data processing system includes a features permutations testing function that separates out from among a set of identified compound features, those compound feature permutations that have better capabilities for distinguishing between anomalies observed in respective multi-dimensional feature spaces having as their axes the features of the identified compound features.