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现今的统计学习虽然已经有了重大的发展,但是若想把事情完全交给机器完成却不能得到理想结果,仍需要加入大量的人类智慧。现代统计学习理论是研究利用经验数据进行机器学习的一般理论,属于计算机科学、模式识别和应用统计学相交叉与结合的范畴。在科学技术飞速发展的今天,统计学习理论广泛吸收和融合相关学科的新理论,不断开发应用新技术和新方法,深化和丰富了统计学传统领域的理论与方法,并拓展了新的领域。
Although significant progress has been made in statistical learning today, it is still necessary to add a great deal of human intelligence to getting things done to the machine without achieving the desired results. Modern statistical learning theory is to study the use of empirical data for the general theory of machine learning, belonging to the category of computer science, pattern recognition and applied statistics cross and the combination of. With the rapid development of science and technology, statistical learning theory absorbs and integrates new theories of related disciplines extensively, develops and applies new technologies and methods, deepens and enriches the theories and methods in the field of statistics and expands new fields.