首页|Research from Dokuz Eylul University Yields New Findings on Machine Learning [A New Predictive Method for Classification Tasks in Machine Learning: Multi-Clas s Multi-Label Logistic Model Tree (MMLMT)]
Research from Dokuz Eylul University Yields New Findings on Machine Learning [A New Predictive Method for Classification Tasks in Machine Learning: Multi-Clas s Multi-Label Logistic Model Tree (MMLMT)]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news reporting out of Izmir, Turkey, by NewsRx ed itors, research stated, “This paper introduces a novel classification method for multi-class multi-label datasets, named multi-class multi-label logistic model tree (MMLMT).” The news journalists obtained a quote from the research from Dokuz Eylul Univers ity: “Our approach supports multi-label learning to predict multiple class label s simultaneously, thereby enhancing the model’s capacity to capture complex rela tionships within the data. The primary goal is to improve the accuracy of classi fication tasks involving multiple classes and labels. MMLMT integrates the logis tic regression (LR) and decision tree (DT) algorithms, yielding interpretable mo dels with high predictive performance. By combining the strengths of LR and DT, our method offers a flexible and powerful framework for handling multi-class mul ti-label data. Extensive experiments demonstrated the effectiveness of MMLMT acr oss a range of well-known datasets with an average accuracy of 85.90% . Furthermore, our method achieved an average of 9.87% improvement compared to the results of state-of-the-art studies in the literature.”
Dokuz Eylul UniversityIzmirTurkeyE urasiaCyborgsEmerging TechnologiesMachine Learning
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