Prediction model training method and device, storage medium and computer equipment

• Main Authors: WANG JIANMING, HUANG BO, WU ZHENYU, BI YE
• Format: Patent
• Language: Chinese; English
• Published: 15.11.2019
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a prediction model training method and device based on a neural network, a storage medium and computer equipment, and mainly aims to reduce the number of manually labeled samples and avoid a large amount of repeated labor, thereby improving the training efficiency and prediction precision of a prediction model. The method comprises the steps of obtaining labeled sample dataand unlabeled sample data; inputting the labeled sample data into a preset neural network model for training to obtain a preliminary model corresponding to the prediction model; inputting the unlabeled sample data into the preliminary model for prediction to obtain confidence coefficients of the unlabeled sample data corresponding to each prediction category; determining a prediction category ofwhich the confidence does not meet a preset condition, selecting unlabeled sample data under the determined prediction category for labeling, and updating the labeled sample data by utilizing newly labeled sample data; and inp