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数据挖掘与机器学习算法

Data mining and Machine learning algorithms
课程网址: http://videolectures.net/aibootcamp2011_balcazar_dmml/  
主讲教师: José L. Balcázar
开课单位: 加泰罗尼亚政治大学
开课时间: 2011-03-31
课程语种: 英语
中文简介:
今天这些讲座的目的是回顾一些相当基本的机器学习算法, 同时试图从数据挖掘的角度来看待它们。因此, 我们将讨论建模的概念、它在从数据中发现知识过程中的作用, 以及这一特定背景的一些特殊性。我们将经历两个 "描述性建模" 过程, 即 k 均值聚类和关联规则挖掘;我们将讨论 "预测建模" 的一些概括性, 如基于 roc 的评价和偏差权衡, 并讨论一些特定的简单分类器: na ï ve bayes, 最近的邻域, 线性分类器,扩展使用内核, 和 adaboost 转移。
课程简介: The purpose of these lectures today is to review a few rather basic Machine Learning algorithms, while trying to see them from a Data Mining perspective. Thus, we will discuss the very notion of modelling, its role within the process of Knowledge Discovery from Data, and some of the particularities of this specific context. We will go through two "descriptive modelling" processes, namely k-means clustering and association rule mining; we will discuss some generalities about "predictive modelling", such as ROC-based evaluation and the bias-variance trade-off, and discuss some specific simple classifiers: naïve Bayes, nearest neighbours, linear classifiers, their extension using kernels, and the Adaboost metapredictor.
关 键 词: 数据挖掘; 机器学习算法; 线性分类器
课程来源: 视频讲座网
最后编审: 2020-06-03:张荧(课程编辑志愿者)
阅读次数: 94