In order to improve the performance by reducing the number of classes for each classifier, we propose to use hierarchical classifiers according to the question ...
May 2, 2025 · Improve accuracy by adding data, treating missing/outlier values, feature engineering, feature selection, multiple algorithms, algorithm tuning ...
Classification: Accuracy, recall, precision, and related metrics
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Aug 25, 2025 · Learn how to calculate three key classification metrics—accuracy, precision, recall—and how to choose the appropriate metric to evaluate a ...
Jan 3, 2017 · Some methods to enhance a classification accuracy, talking generally, are: 1 - Cross Validation : Separe your train dataset in groups, always separe a group ...
We achieve an accuracy of 97.2%, close to a 6 point improvement over the previous State of the Art of 91.6%. Additionally, we believe that machine learning ...
The results demonstrate that ML models outperformed DL models, achieving a best accuracy of 0.871 and F1 score of 0.872. Additionally, domain-specific term ...
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The proposed framework is grammar-based, which involves using the grammatical pattern for each question and using machine learning algorithms to classify them.
Feb 9, 2023 · So I am working on this project and I am doing a classification prediction using a dataset with over 100,000 rows.
Aug 20, 2025 · You can calculate accuracy by dividing the number of correct predictions by the total number of predictions. In other words, accuracy answers ...
Deep ensemble methods combine the predictions of multiple models to improve robustness, accuracy, and uncertainty estimation. By leveraging the strengths of ...
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