17937767. DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT) simplified abstract (Microsoft Technology Licensing, LLC)
Contents
- 1 DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT)
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT) - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT)
Organization Name
Microsoft Technology Licensing, LLC
Inventor(s)
Laurent Boue of Petah Tikva (IL)
DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT) - A simplified explanation of the abstract
This abstract first appeared for US patent application 17937767 titled 'DETERMINATION OF AN OUTLIER SCORE USING EXTREME VALUE THEORY (EVT)
Simplified Explanation
In a patent application, a subset of data is selected from a dataset, and an extreme value theory (EVT) algorithm is used to determine a probability value for a feature in the subset. An outlier score is then generated for the feature based on this probability value, and if the score is above a threshold, the subset is identified as anomalous.
- Subset of data selected from a dataset
- Extreme value theory (EVT) algorithm used to determine probability value for a feature
- Outlier score generated based on probability value
- Anomalous subset identified if outlier score is above threshold
Potential Applications
This technology could be applied in various industries such as finance, cybersecurity, and healthcare for anomaly detection in datasets.
Problems Solved
This technology helps in identifying anomalies in data that may indicate potential issues or abnormalities that need to be addressed.
Benefits
The technology provides a systematic approach to detecting anomalies in data, which can help in improving decision-making processes and identifying potential risks.
Potential Commercial Applications
"Anomaly Detection Technology for Enhanced Data Security and Risk Management"
Possible Prior Art
There may be existing technologies or methods for anomaly detection in data, such as statistical approaches or machine learning algorithms.
Unanswered Questions
How does this technology compare to existing anomaly detection methods?
This article does not provide a comparison with other anomaly detection methods or technologies.
What are the specific parameters used in the EVT algorithm for determining the probability value?
The article does not delve into the specific parameters used in the EVT algorithm for determining the probability value.
Original Abstract Submitted
A subset of data that includes a feature may be selected from a dataset. Parameters from the selected subset of data are determined and an extreme value theory (EVT) algorithm is implemented to determine a probability value for the feature based at least in part on the determined parameters. Based on the determined probability value for the feature, an outlier score is generated for the feature. Based on the outlier score being above a threshold, the subset is identified as anomalous.
