返回到 Meaningful Predictive Modeling
University of California San Diego

Meaningful Predictive Modeling

This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better? By the end of this course you will be familiar with diagnostic techniques that allow you to evaluate and compare classifiers, as well as performance measures that can be used in different regression and classification scenarios. We will also study the training/validation/test pipeline, which can be used to ensure that the models you develop will generalize well to new (or "unseen") data.

状态:Classification Algorithms
状态:Supervised Learning
中级课程小时

精选评论

PT

5.0评论日期:Mar 31, 2021

The course provided a lot of insights into predictive modeling.

NS

4.0评论日期:Nov 16, 2019

Excellent content, but presentation is a bit challenging at times.

所有审阅

显示:10/10

surendar ramamoorthy
2.0
评论日期:Jun 29, 2019
Padam Jung Thapa
5.0
评论日期:Mar 31, 2021
SNIGDHA KHANNA
5.0
评论日期:May 7, 2021
ANUSHREE CHAKRABORTY
5.0
评论日期:Mar 24, 2021
oriol pi
5.0
评论日期:Sep 16, 2019
韓. 彬
5.0
评论日期:Jan 3, 2026
Sudhananda Pal
5.0
评论日期:Apr 14, 2021
Neil Shrubak
4.0
评论日期:Nov 17, 2019
J Nahshon Bright Patten
4.0
评论日期:Jun 30, 2020
SANTIAGO ORTIZ CEBALLOS
3.0
评论日期:Jul 5, 2020