Soft Margin SVM 
Soft Margin SVM
by Harrison Kinsley
Video Lecture 31 of 42
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Views: 1,132
Date Added: August 11, 2016

Lecture Description

In reality, you may find that you either cannot find a linearly separable dimension for your dataset for machine learning, or you may find that your support vector machine has significant overfitment to your data. You know you have over-fitment if you have a large percentage of your dataset as support vectors. The soft-margin SVM allows for some "wiggle room" with separation.

Course Index

Course Description

The objective of this course is to give you a holistic understanding of machine learning, covering theory, application, and inner workings of supervised, unsupervised, and deep learning algorithms.

In this series, we'll be covering linear regression, K Nearest Neighbors, Support Vector Machines (SVM), flat clustering, hierarchical clustering, and neural networks.


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