Linked Questions
21 questions linked to/from Why use gradient descent for linear regression, when a closed-form math solution is available?
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sklearn Linear Regression vs Batch Gradient Descent
tldr: Why would sklearn LinearRegression give a different result than gradient descent?
My understanding is that LinearRegression is computing the closed form solution for linear regression (...
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How is the linear regression optimize in R and Python?
I am currently working a lot with R and Python. I am not able to access the C code the the R function lm_fit. I am wondering how is the linear regression optimize in R and python ?
I am pretty sure ...
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Is stochastic gradient descent unable to learn more complex models which batch gradient descent can learn?
Here's a toy dataset.
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Linear Regression using Matrices vs. Covariance(x,y) / Var(x)
From taking some online linear regression courses (Stanford Machine Learning and John Hopkins Linear Regression) it seems that there are at least three ways of finding a the coefficients of a linear ...
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The best line fit can be found analytically by the least squares method. So can we say that linear regression (least squares) has an optimizer?
The best line fit can be found analytically by the least squares method. So can we say that linear regression (least squares) has an optimizer?
For example, for logistic regression I can use an ...
user162200
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Linear least squares algorithms
I have stumbled across these two questions and accepted answers:
(1) Do we need gradient descent to find the coefficients of a linear regression model?
(2) Why use gradient descent for linear ...
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