The utility model relates to a learning machine for children, which discloses that a pan fixing position of the voice message learning card is positioned on the engine block box which is under the writing board of the active page. The side wall of the pan fixing position one side is ...
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It is important for clinical practice to differentiate between conditions displaying similar symptoms via established diagnostic instruments. Applying the LightGBM algorithm in machine learning, we were able to differentiate subjects with ADHD, obesity, problematic gambling, and a control group using all ...
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To automate tedious cognitive tasks, such as classification, supervised machine learning methods (including interpretable ones [1]) have been recently proposed. Although these methods have been shown to be successful at binary (two-class) classification [2], [3] (e.g. classifying textual fragments...
based on the principles of statistical learning theory, they have been adapted to accomplish regression analysis tasks as well28. As under the most common classification approach, the learning stage of a SVM algorithm for regression is based on the principle of structural risk minimisation. This way...
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curriculum, therefore exploring teachers' concept of the subject matter is essential. Teachers' conception should consist of machine learning subject matters and cognitive methods expected to affect their decision making and not only their conceptions of students, class, society, and emotions [20,24]....
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2.1.5Machine Learning-Based Approaches Machine learning represents another alternative for detecting design defects. Catalet al.[33]used different machine learning algorithms to predict defective modules. They investigated the effect of dataset size, metrics set, and feature selection techniques for softwar...