Feedback information prediction model training method and device and electronic equipment
A technology for estimating models and feedback information, applied in the field of deep learning, can solve problems such as large manpower, computing power, time cost, and low model accuracy
Active Publication Date: 2022-07-29
BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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[0004] However, the above methods often require a lot of manpower, computing power and time costs, and cannot ensure that the selected features can bring benefits to the model, resulting in low accuracy of the trained model
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[0086] In order to make those skilled in the art better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
[0087] It should be noted that the terms "first", "second" and the like in the description, claims and drawings of the present disclosure are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the disclosure described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the illustrative examples below are not intended to represent all implementations consistent with this disclosure. Rather, they are merely examples of apparatus and methods consistent wi...
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The invention relates to a feedback information prediction model training method and device and electronic equipment, and belongs to the technical field of deep learning, and the method comprises the steps: obtaining a first feature set and a sample data set, and carrying out the calibration of a prediction result outputted by a feedback information prediction model according to a calibration model corresponding to the feature of each dimension in the first feature set, and obtaining a calibration result of the sample data set, determining at least one target feature from the first feature set based on the calibration result, and adding the target features into a training process of the feedback information estimation model. Wherein the accuracy of the calibration result obtained based on the calibration model corresponding to the target feature is greater than the accuracy of the pre-estimation result, which indicates that a more accurate result can be obtained by calibrating the pre-estimation result through the calibration model, so that the feature corresponding to the calibration model is added into the training process of the feedback information pre-estimation model, and the accuracy of the pre-estimation result is improved. And the iteration efficiency of model training and the accuracy of the model can be effectively improved.
Description
technical field [0001] The present disclosure relates to the technical field of deep learning, and in particular, to a feedback information prediction model training method, device, and electronic device. Background technique [0002] With the maturity of deep learning technology, deep learning has replaced traditional machine learning algorithms and has become the technology of choice in machine learning. The essence of deep learning is to build a machine learning model with many hidden layers and use massive training data for model training to learn more useful features, thereby improving the accuracy of model output. [0003] In the related art, in order to improve the performance of the model, a feature selection method is often used to optimize the feature set of the model. For example, manual selection by technicians based on parameters such as missing rate, relevance, and informative value of features. For another example, through data dimensionality reduction, the ...
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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/04G06F18/214
Inventor 应元翔谢淼解浪
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD