特色建设Feature construction |
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课程网址: | http://videolectures.net/bootcamp07_guyon_fcon/ |
主讲教师: | Isabelle Guyon |
开课单位: | 克洛平公司 |
开课时间: | 2007-11-06 |
课程语种: | 英语 |
中文简介: | 本课程涵盖功能选择基础和应用程序。首先会提醒学生机器学习算法的基础知识和过度拟合避免的问题。在包装器设置中,将引入特征选择作为模型选择问题的特殊情况。将审查导出原则特征选择算法的方法以及启发式方法,这些方法在实践中很有效。一节课将专门介绍特征构造技术。最后,讲座将专门讨论功能部分和因果发现之间的联系。课程将伴随几个实验课程。该课程对喜欢玩数据并希望学习实用数据分析技术的学生具有吸引力。该教师在模式识别和机器学习方面拥有十年的美国创业公司咨询经验。将提供来自各种应用领域的数据集:手写识别,医学诊断,药物发现,文本分类,生态学,营销。使用特征选择挑战的Gisette数据集进行播放。看看如何通过简单的特征提取方法,可以在纯粹的“不可知”上改进性能。做法。 |
课程简介: | This course covers feature selection fundamentals and applications. The students will first be reminded of the basics of machine learning algorithms and the problem of overfitting avoidance. In the wrapper setting, feature selection will be introduced as a special case of the model selection problem. Methods to derive principled feature selection algorithms will be reviewed as well as heuristic method, which work well in practice. One class will be devoted to feature construction techniques. Finally, a lecture will be devoted to the connections between feature section and causal discovery. The class will be accompanied by several lab sessions. The course will be attractive to students who like playing with data and want to learn practical data analysis techniques. The instructor has ten years of experience with consulting for startup companies in the US in pattern recognition and machine learning. Datasets from a variety of application domains will be made available: handwriting recognition, medical diagnosis, drug discovery, text classification, ecology, marketing. Play with the Gisette dataset of the feature selection challenge. See how with simple feature extraction methods, performances can be improved over the pure “agnostic” approach. |
关 键 词: | 特征选择算法; 建设技术特征; 模式识别; 机器学习 |
课程来源: | 视频讲座网 |
最后编审: | 2020-07-30:yumf |
阅读次数: | 66 |