强所 发表于 2025-3-23 13:27:28
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Textbook 20172nd editionmples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way易达到 发表于 2025-3-24 05:37:47
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https://doi.org/10.1007/978-3-8350-9083-5at it takes to induce a useful classifier from data, and, conversely, why the outcome of a machine-learning undertaking so often disappoints. And so, even though this textbook does not want to be mathematical, it cannot help introducing at least the basic concepts of the ..并置 发表于 2025-3-24 21:40:15
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Die Unbeherrschtheit bei Platonge, offering diverse points of view that complement each other to the point where they may inspire innovative solutions. Something similar can be done in machine learning, too. A group of classifiers is created in a way that makes each of them somewhat different. When they vote about the recommended