Support Vector Regression vs. Linear Regression - Cross Validated
Dec 5, 2023 · Linear regression can use the same kernels used in SVR, and SVR can also use the linear kernel. Given only the coefficients from such models, it would be impossible to distinguish …
regression - What does it mean to regress a variable against another ...
Dec 21, 2016 · Those words connote causality, but regression can work the other way round too (use Y to predict X). The independent/dependent variable language merely specifies how one thing depends …
regression - Why do we say the outcome variable "is regressed on" the ...
Apr 15, 2016 · The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x and y. So, this …
How to choose reference category of predictors in logistic regression ...
Feb 1, 2024 · I am struggling to decide which reference category I should define in my logistic regression model. When I define "mandatory school" as a reference in the variable …
python - Why is R² not equal to the square of Pearson's correlation ...
Apr 21, 2025 · The Journal of Multivariate Analysis specifies that regression using multiple features to predict one outcome is outside of their scope. Submissions dealing with univariate models, including …
How to adjust regression models for selection bias?
Feb 20, 2025 · I am trying to better understand how regression models can be made to correct against different biases within the data. For example, consider the following situation: I have a list of …
What is the lasso in regression analysis? - Cross Validated
Oct 19, 2011 · LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously. This method uses a penalty which affects they value of …
regression - When is R squared negative? - Cross Validated
Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is equivalent to …
How should outliers be dealt with in linear regression analysis ...
What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?
Why Isotonic Regression for Model Calibration?
Jan 27, 2025 · 1 I think an additional reason why it is so common is the simplicity (and thus reproducibility) of the isotonic regression. If we give the same classification model and data to two …