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In sklearn.linear_model.LogisticRegression, there is a parameter C according to docs

Cfloat, default=1.0 Inverse of regularization strength; must be a positive float. Like in support vector machines, smaller values specify stronger regularization.

I can not understand it? What does this mean? Is it λ we multiply when penalizing weights?

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Exactly as it says in the documentation; it's $1/\lambda$, where $\lambda$ is the regularization strength.

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