|
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.
|
Video Length: 4500
Date Found: April 01, 2011
Date Produced: March 31, 2011
|
|
VideoLectures |
July 10, 2011
The explosion in growth of the Web of Linked Data has provided, for the first time, a plethora of information in disparate locations, yet bound together by machine-readable, semantically typed relations. Utilisation of the Web of Data has been, until now, restricted to members of the community, ...
|
VideoLectures |
July 10, 2011
Problems cannot be solved with the mentality that has caused them’. Hence, the 2008- crisis cannot be solved with ethics of one-sided and short-term mentality of the industrial and neoliberal economics, which has caused the ‘Bubble Economy’ of several recent decades. Neither the market nor the ...
|
VideoLectures |
July 10, 2011
|
VideoLectures |
July 10, 2011
|
VideoLectures |
July 10, 2011
Social media presents unique challenges for topic classification, including the brevity of posts, the informal nature of conversations, and the frequent reliance on external hyperlinks to give context to a conversation. In this paper we investigate the usefulness of these external hyperlinks ...
|
|
|
|
|
|
Featured Content
Featuring websites that enhance the internet user’s experience.
|