|
In this second video, we motivate why it is useful to reduce the dimensionality of your data, and describe how this can be done linearly, using a transformation matrix. We describe a setup whereby we…
|
|
Machine Learning Practical (MLP) Lecture 07, Clip 06 / 09.
Course Code
INFR11132 Licence Type
All rights reserved Language
English
|
|
Unsupervised Learning
Course Code
GLHE11086 Licence Type
Creative Commons - Attribution Share A Like
|
|
Sampling - Week 4
Course Code
PA1.2x Evaluation of Predictive Modelling Licence Type
Creative Commons - Attribution Share A Like Language
English
|
|
Pros and cons of dimensionality reduction
Licence Type
Creative Commons - Attribution
|
|
How many principal components to use
Licence Type
Creative Commons - Attribution
|
|
Why we maximize variance in PCA
Licence Type
Creative Commons - Attribution
|
|
Tackling the curse of dimensionality
Licence Type
Creative Commons - Attribution
|
|
The curse of dimensionality
Licence Type
Creative Commons - Attribution
|
|
Data manifolds in high-dimensional spaces
Licence Type
Creative Commons - Attribution
|
|
Pros and cons of nearest-neighbor methods
Licence Type
Creative Commons - Attribution
|