Task: Demonstrate the Effect of Regularization Strength (C) in Logistic Regression
Task: Demonstrate the Effect of Regularization Strength (C) in Logistic Regression: a task in Terminal-Lego-15k (Harbor dataset). The parameter C in scikit-learn's LogisticRegression is the inverse of regularization strength . Regularization is a technique used to prevent overfitting by penalizing…
The task
The parameter `C` in scikit-learn's `LogisticRegression` is the **inverse of regularization strength**. Regularization is a technique used to prevent overfitting by penalizing large model coefficients. A smaller value of `C` means stronger regularization (more penalty on large coefficients), while a larger value of…
Part of PrimeIntellect/Terminal-Lego-15k.