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Questions - manhattan

Manhattan Matrix by 2 Matrices is non symmetric but should be

I created two matrices that have random integers as components, the dimension of the matrix doesn't matter. Then I want to calculate the distance matrix by the Manhattan method and frame it as a matri...
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ZZEEZZ

r

cluster-computing

manhattan

Votes: 0

Answers: 1

Latest Answer

You can make a symmetrical distance matrix from V1 or a symmetrical matrix from V2, but the only way to make a symmetric matrix from both of them together is to combine them V12 <- rbind(V1, V2). T...
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dcarlson

Is there any place in scikit-learn Lasso/Quantile Regression source code that L1 regularization is applied?

I could not find where the Manhattan distance of weights is calculated and multiplied with alpha (L1 reg. coefficient) in the Lasso Regression and the Quantile Regression source code of scikit-learn. ...
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Berat Tuna Karlı

scikit-learn

lasso-regression

regularized

quantile-regression

manhattan

Votes: 0

Answers: 1

Latest Answer

I don't believe the loss function (including the regularization penalty) is ever explicitly calculated, no. Instead, the loss function is optimized by coordinate descent, and so we only ever need to a...
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Ben Reiniger

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