This article discusses the TF-IDF modeling method for converting given text data into a vector quantity for further classification. Using the TF-IDF modeling method, a cosine classifier for text data is obtained. This classifier can be used not only for classifying text data but also for classifying arbitrary vector data. The use of the obtained modeling and classification results with other methods allows determining the most effective classification method.
| Mualliflar | Raxmanov , Asqar, Abduvaliyeva , Zebiniso |
|---|---|
| Jurnal | Pioneering Studies and Theories |
| Nashr sanasi | 2025-03-10 |
| Jild | 1 |
| Son | 4 |
| Betlar | 12-16 |
| Til | Ingliz |
| DOI | 10.5281/zenodo.15046299 |
DOI: 10.5281/zenodo.15046299 · Maqolaning asl sahifasi
Classification, vector, nearest neighbor method, Word2Vec, SVM, Apollon's sphere, BOW, TF-IDF
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