# Questions tagged [lasso]

Use for questions about Lasso (least absolute shrinkage and selection operator), the regularization method for regression models.

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29 views

### regarding lasso.score in lasso modeling using scikit-learn

I once saw the following code segment of using lasso model based on scikit-learn ...
22 views

### Generating artificial data to extend learning set

I have dataset containing 42 instances(X) and one final Y on which i want to perform LASSO regression.All are continuous and numerical. As the sample size small, I wish to extend it. I am kind of ...
75 views

### How do standardization and normalization impact the coefficients of linear models?

One benefit of creating a linear model is that you can look at the coefficients the model learns and interpret them. For example, you can see which features have the most predictive power and which do ...
42 views

### How is learning rate calculated in sklearn Lasso regression?

I was applying different regression models to Kaggle Housing dataset for advanced regression. I am planning to test out lasso, ridge and elastic net. However, none of these models have learning rate ...
11 views

### Can we use both ridge-lasso and PCA in the same model for better results?

My question here is if we are using the PCA, the dimensionality is reduced and no question of feature selection is required using ridge & lasso. So should I use ride-lasso followed by PCA or I ...
17 views

### How to re scale log transformation followed by standard scaling of predicted variables to original scale in python?

I am new to python programming, I was working on Linear regression and followed the below steps Initially took log transformation to convert data to Gaussian distribution Then utilized standard ...
14 views

### Lasso stricter with more data

I am currently analyzing investment strategies, and have implemented a backtest accordingly. This essentially means that I predict returns each month by using all prior historical data. Consequently, ...
94 views

### For a square matrix of data, I achieve $R^2=1$ for Linear Regression and $R^2=0$ for Lasso. What's the intuition behind?

For a square matrix of random data, N columns and N rows. I am fitting two models, linear regression and Lasso. For the linear regression, I achieve a perfect score in train set, while in the Lasso I ...
16 views

### When should we start using stacking of models?

I am solving a Kaggle contest and my single model has reached score of 0.121, I'd like to know when to start using ensembling/stacking to improve the score. I used lasso and xgboost and there ...
32 views

### Normalisation results in R^2 score of 0 - Lasso regression

I am running a regression analysis on a 7000 row dataset with a train/test split of 70%/30%. I am using one variable X to predict a variable ...
33 views

### Scikit-compatible network lasso implementation

Is anyone aware of a scikit-compatible network Lasso (nLasso) implementation? These papers have source code as well: D. Hallac, J. Leskovec, and S. Boyd, “Network lasso: Clustering and ...
62 views

### LASSO remaining features for different penalisation

I am using the sklearn LASSOCV function and I am changing the penalisation parameter in order to adjust the number of features killed off. For example for $\alpha = 0.01$ I have 55 features remaining ...
143 views

### Why does Lasso behave “erratically” when the number of features is greater than the number of training instances?

From the book "Hands-on Machine Learning with Scikit-Learn and TensorFlow 2nd edition" chapter 4: In general, Elastic Net is preferred over Lasso since Lasso may behave erratically when the ...