DEFECT PREDICTION METHOD AND APPARATUS
First Claim
1. A defect prediction method, comprising:
- selecting a training attribute set from a pre-stored product fault record according to a target attribute, and combining the target attribute and the training attribute set into a training set, wherein the target attribute is a defect attribute of a historical faulty product;
generating a classifier set according to the training set, wherein the classifier set comprises at least two tree classifiers; and
predicting a defect of a faulty product by using the classifier set as a prediction model.
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Abstract
Embodiments of the present invention disclose a defect prediction method and apparatus, which relate to the data processing field, and implement accurate and quick locating of a defect in a faulty product. A specific solution is as follows: selecting a training attribute set from a pre-stored product fault record according to a target attribute, and combining the target attribute and the training attribute set into a training set, where the target attribute is a defect attribute of a historical faulty product; generating a classifier set according to the training set, where the classifier set includes at least two tree classifiers; and predicting a defect of a faulty product by using the classifier set as a prediction model. The present invention is used in a process of predicting a defect of a faulty product.
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Citations
18 Claims
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1. A defect prediction method, comprising:
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selecting a training attribute set from a pre-stored product fault record according to a target attribute, and combining the target attribute and the training attribute set into a training set, wherein the target attribute is a defect attribute of a historical faulty product; generating a classifier set according to the training set, wherein the classifier set comprises at least two tree classifiers; and predicting a defect of a faulty product by using the classifier set as a prediction model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A defect prediction apparatus, comprising:
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a processing unit, configured to select a training attribute set from a pre-stored product fault record according to a target attribute, and combine the target attribute and the training attribute set into a training set, wherein the target attribute is a defect attribute of a historical faulty product; a generating unit, configured to generate a classifier set according to the training set that is obtained by the processing unit, wherein the classifier set comprises at least two tree classifiers; and a predicting unit, configured to predict a defect of a faulty product by using the classifier set, which is generated by the generating unit, as a prediction model. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification