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- W4207036342 abstract "Abstract Machine learning is widely used in the field of natural language processing. Text classification is an important branch of natural language processing, mainly utilized to determine the topic of news information and judge the emotional tendency reflected by social data. However, with the expansion of data scale, traditional machine learning algorithms will encounter various performance bottlenecks due to the limitation of single node resource. The machine learning library ML provided by the distributed memory computing framework spark can efficiently process large-scale datasets. Based on Spark ML, this paper uses logistic regression to classify the preprocessed data originated from standard dataset 20newsgroups. The classification accuracy and F1-score can reach 89.64% and 89.64% respectively. Meanwhile, 5-fold cross validation experiments prove that the result is reliable and procedure design is feasible." @default.
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- W4207036342 date "2022-01-01" @default.
- W4207036342 modified "2023-09-26" @default.
- W4207036342 title "Large-scale Text Multiclass Classification Using Spark ML Packages" @default.
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- W4207036342 doi "https://doi.org/10.1088/1742-6596/2171/1/012022" @default.
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