Interpretable time sequence prediction model training method and device and computing equipment

A time series prediction and training method technology, applied in the field of deep learning, can solve problems such as limiting model prediction performance, and achieve the effect of improving prediction performance

Active Publication Date: 2021-12-10
BEIJING REALAI TECH CO LTD
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Problems solved by technology

Although the above methods are easy to explain under the corresponding model assump

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  • Interpretable time sequence prediction model training method and device and computing equipment
  • Interpretable time sequence prediction model training method and device and computing equipment
  • Interpretable time sequence prediction model training method and device and computing equipment

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[0158] As an alternative embodiment, the apparatus may further comprise:

[0159] The acquisition unit is used to obtain any sequence diagram after the training unit is based on the real value and the prediction result, so that the explanatory timing prediction model is trained for the purpose of training the interpretable timing prediction model. ;

[0160] The update unit is used to update the scales of the disturbance region based on the respective features in the sequence diagram to obtain a sequence of sequences corresponding to the sequence diagram.

[0161] Wherein the embodiments of this embodiment may be based on various features a sequence diagram for a target range of the disturbance zone is updated, to thereby obtain a sequence diagram corresponding to the sequence of the saliency map, the sequence significantly FIG clear of interpretable series prediction model explain to enhance the series forecasting model interpretability interpretable.

[0162] Exemplary media

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Abstract

The embodiment of the invention provides an interpretable time sequence prediction model training method and device, a medium and computing equipment. The method comprises the following steps: performing data processing on acquired time sequence data to obtain a sequence diagram corresponding to the time sequence data; modeling the sequence diagram through the interpretable time sequence prediction model to obtain a prediction result corresponding to the sequence diagram; and training the interpretable time sequence prediction model based on a true value and the prediction result in order to improve the prediction precision of the interpretable time sequence prediction model. The multi-dimensional data in the sequence diagram and the time sequence data with the time sequence can be calculated through the interpretable time sequence prediction model, so that the prediction result is output; and the model can be trained based on the prediction result and the true value, so that the model can output a more accurate prediction result, and the prediction performance of the interpretable time sequence prediction model is also improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of deep learning, and more specifically, embodiments of the present invention relate to a training method, device, medium, and computing device for an interpretable time series prediction model. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] Time series data refers to data with a predefined time or order, and time series data can be widely used in various application scenarios, such as classification, prediction, and completion. How to accurately model the influence of each feature of time series data on the prediction results in various application scenarios is a very meaningful problem. At present, the prediction of multidimensional time series corresponding to time series data ...

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Application Information

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IPC IPC(8): G06F30/27G06N3/04G06N3/08
CPCG06F30/27G06N3/04G06N3/08
Inventor 潘庆一胡文波
Owner BEIJING REALAI TECH CO LTD
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