Classification model training method and device, terminal and storage medium
A classification model and training method technology, applied in the field of artificial intelligence, can solve the problem that the classification model cannot effectively eliminate some undesired classification results in advance, and achieve the effect of narrowing the range of prediction results, increasing the difference, and accurate prediction results
Pending Publication Date: 2021-03-09
PING AN TECH (SHENZHEN) CO LTD
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[0004] This application provides a classification model training method, device, terminal and storage medium to solve the problem that the existing classification model cannot effectively eliminate some undesired classification results in advance
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[0020] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.
[0021] The terms "first", "second" and "third" in this application are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature defined as "first", "second", "third" may expressly or implicitly include at least one of that feature. In the description of the present application, "a plurality of" means at least two, ...
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The invention discloses a classification model training method and device, a terminal and a storage medium. The method comprises the steps: building a first task for an expected prediction class and asecond task for an unexpected prediction class in a classification model, inputting a sample into the classification model, obtaining a first prediction probability through the prediction of the first task, and obtaining a second prediction probability through second task prediction; calculating a first loss function value by using the first prediction probability, calculating a second loss function value by using the second prediction probability, and calculating an associated loss function value of the first task and the second task by using the first prediction probability and the second prediction probability; and calculating a final loss function value of the classification model based on the first loss function value, the second loss function value and the associated loss function value, and performing back propagation to update the classification model. According to the method, the classification model is informed of the unexpected prediction category needing to be avoided during prediction in advance, so that the prediction accuracy is improved, and meanwhile, the influence caused by prediction errors is also reduced.
Description
technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular, to a classification model training method, device, terminal and storage medium. Background technique [0002] With the development of technology, the field of artificial intelligence (AI) is developing rapidly, especially with the wide application of deep learning technology, which has made breakthroughs in the fields of object detection and recognition. At present, in the fields of image recognition, speech recognition, voiceprint recognition, etc., basic classification networks are used for training to obtain features, and then further classification is performed to identify the person or voice content to which the input data belongs. The classification model obtained by training in this way has reached a high accuracy rate. However, in real production applications, there are often some special cases. When a category is misclassified as another cate...
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IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/084G06F18/241G06F18/214
Inventor 吴天博王健宗程宁
Owner PING AN TECH (SHENZHEN) CO LTD