Dec 4, 2014 · When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i.e. Y = aX + b Y = a X + b.

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 …

I was just wondering why regression problems are called "regression" problems. What is the story behind the name? One definition for regression: "Relapse to a less perfect or developed state."

I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3.

Jun 30, 2023 · Explicitly, a logistic regression does no classification, instead returning predicted probabilities of event occurrence. However, the machine learning terminology seems to refer to …

86 "..approach classification problem through regression.." by "regression" I will assume you mean linear regression, and I will compare this approach to the "classification" approach of fitting a logistic …

8 For a linear regression, the fitted slope is going to be the correlation (which, when squared, gives the coefficient of determination, the R2 R 2) times the empirical standard deviation of the regressand …

Oct 3, 2021 · Although one can compute a single regression for all data points, if you include model assumptions such as i.i.d. normal errors, the for all points combined can't be "correct" if the four …

Feb 4, 2025 · Belsley (1980) mentioned how DFBETA are calculated for linear regression models "DFBETA values are usually calculated via equations that relate the least-squares fit of a …

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