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2018-04-12
Ease of filling the forms. There is one change if you can make will be great... in date of birth column, once you click on it, you have to put the MM/DD/YYYY. If you can allow to override that and just put the year, that will be of help. In my case where my father was born in 1920 and his date of MM/DD is not known, I'm forced to fill it with incorrect information.
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2019-07-24
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2020-06-10
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What is a good log loss score?
The bolder the probabilities, the better will be your Log Loss closer to zero. It is a measure of uncertainty (you may call it entropy), so a low Log Loss means a low uncertainty/entropy of your model. Log Loss is similar to the Accuracy, but it will favor models that distinguish more strongly the classes.
What is log loss and how it helps to improve performance?
Log-loss is an appropriate performance measure when your model output is the probability of a binary outcome. The log-loss measure considers confidence of the prediction when assessing how to penalize incorrect classification.
What is a good log loss?
The bolder the probabilities, the better will be your Log Loss closer to zero. It is a measure of uncertainty (you may call it entropy), so a low Log Loss means a low uncertainty/entropy of your model. Log Loss is similar to the Accuracy, but it will favor models that distinguish more strongly the classes.
What is a log loss?
Logarithmic Loss, or simply Log Loss, is a classification loss function often used as an evaluation metric in Gaggle competitions. Log Loss quantifies the accuracy of a classifier by penalizing false classifications.
What is the range of log loss metric?
Logarithmic loss (related to cross-entropy) measures the performance of a classification model where the prediction input is a probability value between 0 and 1. The goal of our machine learning models is to minimize this value. A perfect model would have a log loss of 0.
Why do we use cross entropy loss?
Cross Entropy is definitely a good loss function for Classification Problems, because it minimizes the distance between two probability distributions — predicted and actual. So cross entropy make sure we are minimizing the difference between the two probability. This is the reason.
What is a log loss function?
Logarithmic Loss, or simply Log Loss, is a classification loss function often used as an evaluation metric in Gaggle competitions. Minimizing the Log Loss is basically equivalent to maximizing the accuracy of the classifier, but there is a subtle twist which we'll get to in a moment.
What is loss function in statistics?
What is a loss function in statistics? A loss function is a measure of the cost of not making the best decision. It is usually regarded as an opportunity loss, so if the best decision would give you a profit of $20 and another decision would give a profit of $5, the opportunity loss for that decision is $15.
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