All Questions
Tagged with cross-entropy logistic-regression
9 questions
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Why don't I get the same result as with tensorflow's method when I write my own expression?
I'm learning logistic regression and I want to calculate what is the value of the cross entropy loss function during minimizing it via gradient descent, but when I use tensorflow's ...
- 124
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How is error calculated in a simple logistic regression neural network?
Below is the following dataframe reporting the results of training a dataset on a binary classification problem:
columns a and b represent x and y respectively and the structure of the neural network ...
- 302
-1
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Difference between Logistic Loss and Cross Entropy Loss
I'm confused about logistic loss and cross entropy loss in binary classification scenario.
According to Wikipedia (https://en.wikipedia.org/wiki/Loss_functions_for_classification), the logistic loss ...
- 1,177
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2
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How to write custom CrossEntropyLoss
I am learning Logistic Regression within Pytorch and to better understand I am defining a custom CrossEntropyLoss as below:
def softmax(x):
exp_x = torch.exp(x)
sum_x = torch.sum(exp_x, dim=1,...
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how to make my logistic regression faster
I have to do simple logistic regression (only in numpy, I can't use pytourch or tensorflow).
Data: part of MNIST
Goal: I should have accuracy about 86%.
Unfortunately i have only about 70%, and my ...
- 593
5
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5
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Comparing MSE loss and cross-entropy loss in terms of convergence
For a very simple classification problem where I have a target vector [0,0,0,....0] and a prediction vector [0,0.1,0.2,....1] would cross-entropy loss converge better/faster or would MSE loss?
When I ...
- 803
101
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How to choose cross-entropy loss in TensorFlow?
Classification problems, such as logistic regression or multinomial
logistic regression, optimize a cross-entropy loss.
Normally, the cross-entropy layer follows the softmax layer,
which produces ...
- 53.8k
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Does binary log loss exclude one part of equation based on y?
Assuming the log loss equation to be:
logLoss=−(1/N)*∑_{i=1}^N (yi(log(pi))+(1−yi)log(1−pi))
where N is number of samples, yi...yiN is the actual value of the dependent variable, and pi...piN is the ...
- 1,575
1
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Need help understanding the Caffe code for SigmoidCrossEntropyLossLayer for multi-label loss
I need help in understanding the Caffe function, SigmoidCrossEntropyLossLayer, which is the cross-entropy error with logistic activation.
Basically, the cross-entropy error for a single example with ...
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