RISK IDENTIFICATION MODEL TRAINING METHOD AND APPARATUS, AND SERVER

摘要

An implementation of the present specification provides a method for training a risk identification model. Because different types of unsupervised machine learning algorithms have different requirements for features, a type of a target unsupervised machine learning algorithm can be determined first, then various types of feature information are extracted from input information, and then target feature information is extracted from the feature information in a way of extracting feature information corresponding to the type of the target unsupervised machine learning algorithm. Because the target feature information adapted to the target unsupervised machine learning algorithm is extracted, a target risk identification model obtained through training by using the target feature information based on the target unsupervised machine learning algorithm has higher identification accuracy and ensures the accuracy of risk identification.