首页|Lund University Reports Findings in Machine Learning (AlphaML: A clear, legible, explainable, transparent, and elucidative binary classification platform for tabular data)
Lund University Reports Findings in Machine Learning (AlphaML: A clear, legible, explainable, transparent, and elucidative binary classification platform for tabular data)
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New research on Machine Learning is the subject of a report. According to news reporting originating from Lund, Sweden, by NewsRx correspondents, research stated, “Leveraging the potential of machine learning and recognizing the broad applications of binary classification, it becomes essential to develop platforms that are not only powerful but also transparent, interpretable, and user friendly. We introduce alphaML, a user-friendly platform that provides clear, legible, explainable, transparent, and elucidative (CLETE) binary classification models with comprehensive customization options.” Our news editors obtained a quote from the research from Lund University, “AlphaML offers feature selection, hyperparameter search, sampling, and normalization methods, along with 15 machine learning algorithms with global and local interpretation. We have integrated a custom metric for hyperparameter search that considers both training and validation scores, safeguarding against under- or overfitting. Additionally, we employ the NegLog2RMSL scoring method, which uses both training and test scores for a thorough model evaluation. The platform has been tested using datasets from multiple domains and offers a graphical interface, removing the need for programming expertise.”
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