This class was created by Brainscape user Jens Waaben. Visit their profile to learn more about the creator.
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Jens Waaben
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Decks in this class (21)
Chapter 1
0
cards
Chapter 2
Name the three attributes,
Name the 3 attribute types,
When to use mean sd normalization
5
cards
Chapter 3
What is a eigenvector
1
cards
Chapter 4
What is data mode,
What does the covariance explain,
What is stemming
4
cards
Chapter 5
What is a stochastic variable,
How do we get probability distrib...,
What is the bernoulli distribution
6
cards
Chapter 6
Purpose of using prop densities,
What is a probability density fun...,
What is a multivariate distribution
6
cards
Chapter 7
0
cards
Chapter 8
What is supervised learning,
What does it mean that the functi...,
How to maximize w in linear regre...
4
cards
Chapter 9
What is a tree leaf node,
How to determine which questions ...,
What is impurity
6
cards
Chapter 10
What is cross validation,
What is the generalization error,
Hold out cross validation
6
cards
Chapter 11
What are the main differences bet...
1
cards
Chapter 12
The principle of k nearest neighbour,
The priciple in knn regression,
What is the classification error
3
cards
Chapter 13
0
cards
Chapter 14
What is the purpose of regulariza...,
What is bias
2
cards
Chapter 15
0
cards
Chapter 16
What is class imbvalance,
What is resampling,
What is penalization
3
cards
Chapter 17
What are ensemble methods,
Overall principle of bagging,
Principle of boosting
4
cards
Chapter 18
Types of distance based clusterin...,
Weaknesses k means,
How to measure a difference in cl...
3
cards
Chapter 19
What is the purpose of the em alg...
1
cards
Chapter 20
One way to find outliers,
What to do with clusters with ver...
2
cards
Chapter 21
What is association rulelearning,
What does support show,
What does confidence show
5
cards
More about
Machine learning
- Class purpose General learning
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