Prediction model training method and device, data prediction method and device and storage medium
A technology for predicting models and training methods, applied in the computer field, can solve problems such as low accuracy rate and poor model generalization ability, and achieve the effect of improving accuracy
Active Publication Date: 2021-04-30
TENCENT TECH (SHENZHEN) CO LTD
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However, the current prediction models established by machine learning algorithms have the problems of low accuracy and poor model generalization ability
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[0075] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0076] Machine learning (Machine Learning, ML) is a multi-field interdisciplinary subject, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. Specializes in the study of how computers simulate or implement human learning behaviors to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent, and its application pervades all...
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The invention relates to a prediction model training method and device, computer equipment and a storage medium. The method comprises the steps of acquiring a training sample set, wherein the training sample set comprises training samples, training sample weights corresponding to the training samples and target energy characteristics corresponding to the training samples; determining a current training sample from the training sample set based on the training sample weight; inputting the current target energy feature corresponding to the current training sample into a pre-training prediction model for basic training, and obtaining a basic prediction model when the basic training is completed; and updating the training sample weight corresponding to each training sample based on the basic prediction model, and performing iterative execution until the model training is completed to obtain a target prediction model which is used for predicting interaction state information corresponding to the input protein information and the input compound information. By adopting the method, the prediction accuracy of the target prediction model obtained by training can be improved.
Description
technical field [0001] The present application relates to the field of computer technology, in particular to a prediction model training, data prediction method, device, computer equipment and storage medium. Background technique [0002] With the development of artificial intelligence technology, there has been the use of machine learning algorithms to predict the affinity between compounds and targeted proteins. At present, the model established by using the machine learning algorithm is used to predict the affinity change between the target protein and the compound after mutation, and then determine whether the target protein is resistant to the compound, so as to provide a reference for doctors to use drugs. However, the current prediction models established by machine learning algorithms have problems of low accuracy and poor model generalization ability. Contents of the invention [0003] Based on this, it is necessary to provide a prediction model training, a data ...
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IPC IPC(8): G16B40/00G06N20/00
CPCG16B40/00G06N20/00G16B15/30G16B40/20G16B20/50G06N20/20G06N5/01G16B15/00G06N5/022
Inventor 杨子翊叶兆丰廖奔犇张胜誉
Owner TENCENT TECH (SHENZHEN) CO LTD