Tagged Questions
-1
votes
1answer
33 views
How logical to select features with respect to the correlation matrix and weigthing?
Is it logical to name low correlated features as valuable and choosing the low corelated ones for classification? Or it depends on the algorithm used for the purpose? How do I need to interpret a ...
0
votes
0answers
58 views
Why does NNLS only pick weakly correlated variables?
I have been looking to find an answer to this problem but haven't had much luck.
My problem has high multicollinearity and hence I am using NNLS (non negative least squares) in R. I am regressing ...
2
votes
2answers
67 views
Can feature selection be considered a way to observe relationship between variables like correlation?
In correlation we can observe relationship between a pair of variables, let me call it X1 and Y.
Now, considering I have the predicting variables X1, X2, ..., Xn and the variable Y. Does the ...
3
votes
0answers
237 views
When does LASSO select correlated predictors?
I'm using the package 'lars' in R with the following code:
...
0
votes
1answer
26 views
Inter-feature ratio explicitly or implicitly?
Let's say I have two numerical features were is suspect that the ratio between them is the most meaningful way of looking at them. I have a NN learner.
Should I add the ratio as a third feature or is ...
2
votes
4answers
224 views
Suggestions for identifying key features
I have a large set of customer data. For these customers, I have devised a customer loyalty score which is a measure of the loyalty of the customer. I want to find the features that are strongly ...
7
votes
1answer
142 views
How to quantify redundancy of features?
I have three features that I use to solve a classification problem. Originally, these features produced boolean values, so I could evaluate their redundancy by looking at how much the sets of positive ...
