Classification method and system for small collections of...

Details Classification method and system for small collections of... Classification method and system for small collections of...

2005-10-18

2008-03-18

Vincent, David (Department: 2129)

Data processing: artificial intelligence

Machine learning

Reexamination Certificate

active

07346594

ABSTRACT:
A method and system for classifying small collections of high value entities with missing data. The invention includes: collecting measurement variables for a set of entity cases for which classifications are known; calibrating standard weights for each measurement variable based on historical data; computing compensating weights for each entity case that has missing data, computing case scores for each of one or more dimensions as a sum-product of compensating weights and variables associated with each dimension; executing an iterative process that finds a specific combination of compensation weights that best classify the entity cases in terms of distinct scores; and applying a resulting model, which is determined by the specific combination of compensation weights, to classify other entity cases for which the classifications are unknown.

REFERENCES:
Derrick A. Bennett “How can I deal with missing data in my study?” Australian and New Zealand Journal of Public Health vol. 25 No. 5 2001.

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