Classification in Machine Learning
When
4 p.m., Nov. 2, 2021
Classification is one main type of supervised learning, where the task is to categorize a set of data into different classes based on their attributes. I will first introduce the concept of the Bayes classifier from the perspective of learning theory. Then several commonly used linear and nonlinear classifiers for binary and multiclass classification problems will be reviewed. I will further discuss challenges in classifying high dimensional data, as well as state-of-art methods and algorithms to tackle the curse of dimensionality. Finally, the problem of classifying time-course data will be also discussed, along with real examples.
Place: Math Building, Room 402