Decision tree model construction method and device, electronic equipment and medium

Abstract

The embodiment of the invention provides a decision tree model construction method and device, electronic equipment and a medium, and the method comprises the steps: constructing a word bag model by using a training text; establishing a first decision tree model according to the first characteristic value of each answer text included in the word bag model and an answer score label set for each answer text, and obtaining an importance degree value of the word characteristic of each answer text output by the first decision tree model; according to the importance degree value of the word featureof each answer text, obtaining an answer text, and screening out keyword features meeting preset conditions from the word features of the answer texts, and establishing a second decision tree model for answer score prediction according to the second feature values of the answer texts obtained by the keyword features and the answer score tags set for the answer texts. With the adoption of the application, the scoring prediction precision can be improved, and meanwhile, the interpretability of the model is ensured.

Description

technical field [0001] The present application relates to the field of deep learning, and in particular to a decision tree model construction method, device, electronic equipment and media. Background technique [0002] With the development of science and technology, in order to save the trouble of manual scoring, the intelligent scoring system has emerged as the times require, and has been more and more widely used in schools, enterprises and other institutions. Relevant personnel can manually formulate corresponding rules in the intelligent scoring system, and the intelligent scoring system can use the manually formulated rules to score answers. However, the scoring prediction accuracy achieved by this method is limited. In order to improve the scoring prediction accuracy, some personnel used the machine learning method of logistic regression to score the answers. While machine learning methods using logistic regression can achieve higher rating prediction accuracy, the r...

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Problems solved by technology

While machine learning methods using logistic regression can achieve higher rating prediction accuracy, the resulting models are less interpretable

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