In least-squares models, the cost function is defined as the square of the difference between the predicted value and the actual value as a function of the input.

When we do logistic regression, we change the cost function to be a logarithmic function instead of defining it to be the square of the difference between the sigmoid function (the output value) and the actual output.

Is it OK to change and define our own cost function to determine the parameters?

machine-learning data-mining regression
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