Research on event classification of student community network platform based on machine learning
In recent years,various online platforms have been heavily invested in the construction of"one-stop"student com-munities in colleges and universities.This paper mainly explores the effect of machine learning algorithm in"one-stop"student community network platform event speech classification.This paper mainly uses machine learning algorithms,including K-nearest neighbor,decision tree,polynomial naive Bayes,logistic regression,support vector machine,random forest,lightweight gradient lift-ing,extreme gradient lifting algorithms to construct classification models for short text classification.The results show that the accu-racy of the above algorithm is 0.62,0.74,0.89,0.88,0.85,0.87,0.80,0.82,which shows that the classification has a good effect.
text classificationmachine learningstudent communitynetwork platform
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