NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Confidence-Based Feature AcquisitionConfidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).
Document ID
20100009690
Document Type
Other - NASA Tech Brief
Authors
Wagstaff, Kiri L. (California Inst. of Tech. Pasadena, CA, United States)
desJardins, Marie (Maryland Univ. United States)
MacGlashan, James (Maryland Univ. United States)
Date Acquired
August 25, 2013
Publication Date
March 1, 2010
Publication Information
Publication: NASA Tech Briefs, March 2010
Subject Category
Man/System Technology and Life Support
Report/Patent Number
NPO-46886
Distribution Limits
Public
Copyright
Public Use Permitted.

Available Downloads

NameType 20100009690.pdf STI

Related Records

IDRelationTitle20100009649Analytic PrimaryNASA Tech Briefs, March 2010