Questions tagged [partial-least-squares]
A class of linear methods for modeling the relationship between two groups of variables, X and Y. Includes PLS regression.
274 questions
0 votes
0 answers
22 views
Combining filtering with clr transform
I am working with a compositional dataset: A very efficient way of dealing with compositional data is by applying clr-transform (or a similar), which effectively converts them to data in Eucledean ...
- 5,011
2 votes
1 answer
51 views
Manual calculation prediction from PLS using extracted coeficients
I am performing a PLS prediction using the pls R package (Mevik et al). Some parts of the code are as below: ...
- 263
1 vote
0 answers
46 views
Is it valid to select features for PLS regression using correlation to the target variable?
I am reading a paper. I read that the authors, in order to reduce the number of features their PLS regressor has to handle, have chosen to only retain columns which have some given R^2 correlation to ...
- 227
0 votes
0 answers
49 views
How might I emulate R's selectNcomp in scikit learn?
R's mvr package has a useful function, selectNcomp, for automated selection of retained latent variables in cross-validated PLS models, through implementation of the heuristic one standard error rule:...
2 votes
1 answer
129 views
Partial Least Squares Regression - explained variance for X above 100%
I am modelling daily returns of the S&P 500 using 58 parameters (stock price, past returns, interest rates, treasury yields, commodities...etc.). I created a regression model with Partial Least ...
0 votes
0 answers
63 views
Plausibility of results for PCR/PLSR daily stock return forecasting
I'm working on a project for my master's degree and, I am not sure, whether the results I'm getting are plausible or not. I am basically trying to create a model for forecasting S&P 500 return ...
0 votes
0 answers
26 views
Is PLS appropriate for Predicting Chemical Concentrations from NIR Spectroscopy?
I have a set of NIR spectroscopy data for various beverage samples, each with corresponding concentrations of chemical ingredients (e.g., caffeine). I would like to train a PLS model to predict the ...
2 votes
1 answer
140 views
Predicting a Noisy Target with High-dimensional Features
I am working on a regression problem with two sets of continuous features, $X_1$ and $X_2$ that I assume are useful for predicting a continuous target $y$ that is very noisy. By "noisy" I ...
- 23