The project aims to identify the best model for the classification of texts derived from descriptions of assets subject to Italian judicial auctions. The employed models include conventional models, such as Logistic Regression, Naive Bayes, SVM, and XGBoost, and neural network models such as Fasttext and XLM-Roberta.
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The project aims to identify the best model for the classification of texts derived from descriptions of assets subject to Italian judicial auctions. The employed models include both conventional models, such as Logistic Regression, Naive Bayes, SVM, and XGBoost, and neural network models, such as Fasttext and XLM-Roberta.
alessandromonolo/Descriptive-Texts-Classification-By-Usage-Purposes-Of-Estate-Properties
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The project aims to identify the best model for the classification of texts derived from descriptions of assets subject to Italian judicial auctions. The employed models include both conventional models, such as Logistic Regression, Naive Bayes, SVM, and XGBoost, and neural network models, such as Fasttext and XLM-Roberta.
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