| abstract |
The present application relates to a method and device for constructing a data set, a mobile terminal, and a computer-readable storage medium. The method includes: acquiring a first data set with a first preset quantity and carrying annotation information according to a learning task; training a classification model on the first data set, and evaluating the accuracy information of the classification model; when the accuracy information reaches a preset value , the unlabeled data is classified and screened based on the trained classification model, and the filtered data is merged into the first data set to form the second data set; the data in the second data set is classified and cleaned based on the trained classification model To form a target data set with a target quantity; semi-automatic data collection and screening and labeling can be realized, and a large amount of high-quality data for training classification models can be obtained on the basis of less manpower, which greatly saves labor costs and improves Efficiency in forming a data set. |