An active learning method and device

Abstract

The invention discloses an active learning method and device. The method comprises the following steps: obtaining labeled sample data; training the labeled sample data by using a machine learning model to obtain an intermediate model; inputting test data into the intermediate model for prediction to obtain a prediction result corresponding to the test data; outputting the test data corresponding to the prediction result of the fuzzy boundary as to-be-labeled sample data according to a preset evaluation index; wherein the machine learning model is trained in a multi-thread parallel mode, and the intermediate model is used for prediction. The invention provides a machine learning platform with strong universality for a user. According to the method, the labeling amount of sample data used for training of the input model can be reduced, the labor cost of manual labeling is reduced, and the processing efficiency is effectively improved. And the effect of quickly iteratively optimizing themodel at the minimum labeled data cost is achieved. And the minimum consumption of processing resources is realized.

Description

technical field [0001] The invention relates to the technical field of Internet communication, in particular to an active learning method and device. Background technique [0002] In recent years, with the rapid development of a series of Internet technologies such as big data (big data), machine learning (Machine Learning, ML), artificial intelligence (AI), high-performance computing, etc., all walks of life are building services based on the Internet , providing personalized services to hundreds of millions of users through mobile terminals. For Internet-based services, one of the key technologies is to use artificial intelligence and big data capabilities to provide users with personalized services. For example, shopping websites recommend relevant products based on the user's historical shopping behavior, the advertising system recommends appropriate advertisements based on the user's historical click behavior, and the financial system identifies fraudulent transactions...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of low efficiency when labeling sample data in machine learning in the prior art, the present invention provides an active learning method and device:

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