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Titlebook: Computational Intelligence in Data Science; 7th IFIP TC 12 Inter Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P Conference proceedings

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Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P
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https://doi.org/10.1007/978-3-658-27431-3 techniques. Designed for open-source collaboration, this solution is positioned for continuous improvement, adaptation to evolving needs, and addressing emerging challenges in the field of intelligent transportation and related domains. This paper represents a foundational step towards establishing
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Arbeitsbereich Baumanagement – ic regression, SVM, stochastic gradient descent, decision trees, and ensemble models were conducted. In summary, this research contributes significantly to the ongoing battle against online toxicity and the promotion of more constructive online conversations. The RNN algorithm’s 99.47% accuracy rate
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Die digitale Demokratie in der Schweizhese experiments, we attained exceptional F1 scores of 99% for RoBERTa, 98% for AlBERT, and 96% for BERT base. In contrast, traditional models like Logistic Regression achieved 93%, Random Forest 89%, and deep learning models such as LSTM, BiLSTM and CNN achieved 82%, 93% and 90%, respectively. The
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Julian Bubel Dipl.-Ing.,Jürgen Grabend reduce complexity. This is leading to improved classification performance. The proposed work is evaluated on six machine-learning models. The features extracted achieving a consistent AUC-ROC score of 95%. The highest accuracy of 95% on the Cleveland dataset. Our proposed machine learning-based C
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