Market prediction data processing method and device
A technology for market forecasting and processing methods, applied in marketing and other directions, to solve problems such as inaccurate forecast results
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Embodiment 2
[0090] This embodiment provides a processing device for market forecast data, please refer to figure 2 , the device includes:
[0091] The first obtaining module 201 is used to use the preliminary prediction data set obtained in advance as the first training set;
[0092] The first prediction module 202 is configured to use a convolutional neural network model to classify the first training set, and predict the classified first training set to obtain a first prediction result;
[0093] The second obtaining module 203 is configured to add the first prediction result to the classified first training set to obtain a second training set;
[0094]The second prediction module 204 is configured to respectively obtain multiple target prediction sets by using a bagging method according to the second training set, and perform market prediction based on the multiple target prediction sets.
[0095] In the market prediction data processing device provided in the embodiment of the prese...
Embodiment 1
[0104] Various variations and specific examples of the processing method of market forecast data in Embodiment 1 are also applicable to the device of this embodiment. Through the foregoing detailed description of the processing method of market forecast data, those skilled in the art can clearly understand that this The devices in the embodiments are therefore not described in detail here for the sake of brevity.
[0105] Based on the same inventive concept as that of Embodiment 1, the present invention also provides a computer-readable storage medium corresponding to the method for processing market forecast data, see Embodiment 3 for details.
Embodiment 3
[0107] This embodiment provides a computer-readable storage medium 300, on which a computer program 311 is stored, and when the program is executed by a processor, the following steps are implemented:
[0108] Using the preliminary prediction data set obtained in advance as the first training set;
[0109] Classifying the first training set by using a convolutional neural network model, and predicting the classified first training set to obtain a first prediction result;
[0110] adding the first prediction result to the classified first training set to obtain a second training set;
[0111] According to the second training set, a plurality of target prediction sets are respectively obtained by using a bagging method, and market prediction is performed based on the multiple target prediction sets.
[0112] Various variations and specific examples of the method for processing market forecast data in Embodiment 1 are also applicable to the computer-readable storage medium of th...
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