Log Likehood, which direction is better

in Machine Learning in Python / Binary predictors in a logistic regression

Is the log likehood more different than 0 means it's a better model (more negative)? But usually it's more near 0 than the LL null. Isn't a more negative result make it more near the LL null?

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Log Likehood, which direction is better

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