Invention Grant
- Patent Title: Feature selection for deviation analysis
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Application No.: US17497661Application Date: 2021-10-08
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Publication No.: US12079196B2Publication Date: 2024-09-03
- Inventor: Paul O'Hara , Malte Christian Kaufmann , Alan McShane
- Applicant: Business Object Software LTD
- Applicant Address: IE Dublin
- Assignee: BUSINESS OBJECTS SOFTWARE LTD
- Current Assignee: BUSINESS OBJECTS SOFTWARE LTD
- Current Assignee Address: IE Dublin
- Agency: Fountainhead Law Group, PC
- Main IPC: G06F16/23
- IPC: G06F16/23 ; G06F16/215 ; G06F17/18

Abstract:
The present disclosure provides for accurate and efficient identification of candidate features for an input dataset comprising one or more continuous features and one or more categorical features is obtained. A number of categorical feature categories based on the one or more categorical features is determined. Record counts for each of the categorical feature categories are determined. Skew statistics for each category are determined based on the record counts for each of the categorical feature categories. Cardinality skew factors for each of the one or more categorical features are then determined based on the record counts and the skew statistics. A number of the one or more categorical features having the highest cardinality skew factors are selected from among the cardinality skew factors. Then, a top contributor deviation analysis is performed using the selected number of the categorical features having the highest cardinality skew factors.
Public/Granted literature
- US20230113850A1 Feature Selection For Deviation Analysis Public/Granted day:2023-04-13
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