Method and system for creating knowledge and selecting features in a semiconductor device
AssigneeHermes Microvision, Inc.
InventorsJack Y. Jau, Zhaoli Zhang, Wei Fang
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Abstract
A method and system for creating knowledge and selecting features in a supervised classifier is disclosed. The method and system comprises changing a feature space of a plurality of defects and marking at least a portion of the samples of the defects in the feature space. The method and system includes labeling the at least a portion of the samples as training samples, determining if the training samples are of the same type and creating knowledge based upon the training samples if the samples are of the same type.
Claims12
A method for creating knowledge and selecting features for a supervised classifier comprising:
- changing a feature space of a plurality of defects;
- marking at least a portion of the samples of the defects in the feature space;
- labeling the at least a portion of the samples as training samples;
- determining if the training samples are of the same type;
- and
- creating knowledge based upon the training samples if the samples are of the same type.
A method for creating knowledge and selecting features for a supervised classifier comprising:
- changing a feature space of a plurality of defects;
- marking at least a portion of the samples of the defects in the feature space;
- labeling the at least a portion of the samples as a T set element;
- changing the feature space of the T set element;
- deciding upon appropriate parameters;
- determining if the parameters can be used to classify the T set element;
- and
- creating knowledge based upon the parameters if the parameters are used.
A computer readable medium for creating knowledge and selecting features for a supervised classifier comprising:
- changing a feature space of a plurality of defects;
- marking at least a portion of the samples of the defects in the feature space;
- labeling the at least a portion of the samples as training samples;
- determining if the training samples are of the same type;
- and
- creating knowledge based upon the training samples if the samples are of the same type.
A method for creating knowledge and selecting features for a supervised classifier comprising:
- changing a feature space of a plurality of defects;
- marking at least a portion of the samples of the defects in the feature space;
- labeling the at least a portion of the samples as a T set element;
- changing the feature space of the T set element;
- deciding upon appropriate parameters;
- determining if the parameters can be used to classify the T set element;
- and
- creating knowledge based upon the parameters if the parameters are used.
Dependencies are inferred from the claim text.