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Logistic regression

Log-loss function

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Choose the correct function to minimize in the maximum likelihood estimation method (MLE).

Tip: Log-loss is $-\ln(\prod\limits_{i=1}^m p_i^{y_i} \cdot (1-p_i)^{1-y_i})$

Select one option from the list

-\frac{1}{m} \cdot \sum_{i=1}^{m} (y_i \cdot \ln(y_i) + (1-p_i) \cdot \ln(1-y_i))

-\frac{1}{m} \cdot \sum_{i=1}^{m} (y_i \cdot \ln(p_i) - (1-y_i) \cdot \ln(1-p_i))

-\frac{1}{m} \cdot \sum_{i=1}^{m} (y_i \cdot \ln(p_i) + (1-y_i) \cdot \ln(1-p_i))

-\frac{1}{m} \cdot \sum_{i=1}^{m} (y_i \cdot \ln(p_i) + (1+y_i) \cdot \ln(1+p_i))

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