Method and apparatus for training, classification model, mobile terminal, and readable storage medium

Abstract

Provided are a method and apparatus for training a classification model, a mobile terminal, and a computer-readable storage medium. The method includes that: a classification model is trained based on a preset data set until the accuracy of the classification model reaches a standard value, wherein data in the preset data set includes label information; data in the preset data set is identified based on the trained classification model to acquire category information of the data; when the category information of the data is not matched with the label information, the data is cleaned to acquire a cleaned target data set; and the classification model is trained again based on the target data set.

Dependencies are inferred from the claim text.