Search type Search syntax
Tags [tag]
Exact "words here"
Author user:1234
user:me (yours)
Score score:3 (3+)
score:0 (none)
Answers answers:3 (3+)
answers:0 (none)
isaccepted:yes
hasaccepted:no
inquestion:1234
Views views:250
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Favorites infavorites:mine
infavorites:1234
Status closed:yes
duplicate:no
migrated:no
wiki:no
Types is:question
is:answer
Exclude -[tag]
-apples
For more details on advanced search visit our help page
Results tagged with Search options user 171058

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

7
votes
4answers
I'm looking for a Machine Learning course that would give the maths behind algorithms rather than simply teach how to apply them. I've looked at Udacity Into to Machine Learning and Andrew Ng's course …
asked Jul 27 '17 by GingerBadger
3
votes
1answer
When you use a model that has been trained based on the RBF (Gaussian) kernel, do you need to store the entire training dataset to compute similarity features? If so, why doesn't this decrease the eff …
asked Sep 9 '17 by GingerBadger
10
votes
1answer
My understanding of SVM is that it's very similar to a logistic regression (LR), i.e. a weighted sum of features is passed to the sigmoid function to get a probability of belonging to a class, but ins …
asked Sep 11 '17 by GingerBadger
1
vote
1answer
I have some data, which I split into training, cross-validation and test sets. I built two models, that I trained on the training set and optimised using the cross-validation set (e.g. finding the opt …
asked Aug 8 '17 by GingerBadger