The logistic regression definition is The name is regression, but it's actually a classification model, and I've created an example in a situation where predicting a classification is understood.
"Because humidity is ~, the probability of rain is 70%" ==> Regression
"Today is a rainy day" ==> Categorization
"70% chance of rain" => 70% forecast to classify rainy days. => Logistic Regression
Is that right?!?!?! Is that understood correctly?
logistic-regression logistic
Regression is a method of calculating the predicted minimum error for a new value based on the learned model. So if you put an activation function on it and you decide on one label, it's logistic regression.
It's not quite right to understand that "...it's actually a classification model..."
Examples seem appropriate for understanding.
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