Use this tag for programming-related questions about the softmax function, also known as the normalized exponential function.
From the Udacity's deep learning class, the softmax of y_i is simply the exponential divided by the sum of …
python numpy machine-learning logistic-regression softmaxI tried to implement soft-max with the following code (out_vec is a numpy vector of floats): numerator = np.exp(…
python numpy softmaxI recently came across tf.nn.sparse_softmax_cross_entropy_with_logits and I can not figure out what the …
neural-network tensorflow softmax cross-entropyIn the output layer of a neural network, it is typical to use the softmax function to approximate a probability …
math neural-network softmaxI am trying to understand backpropagation in a simple 3 layered neural network with MNIST. There is the input layer with …
python numpy neural-network backpropagation softmaxI am watching some videos for Stanford CS231: Convolutional Neural Networks for Visual Recognition but do not quite understand how …
python numpy softmaxIs there a numerically stable way to compute softmax function below? I am getting values that becomes Nans in Neural …
python numpy nan scientific-computing softmaxI am training a binary classifier using Sigmoid activation function with Binary crossentropy which gives good accuracy around 98%. The same …
binary classification keras softmax sigmoidFor a neural networks library I implemented some activation functions and loss functions and their derivatives. They can be combined …
neural-network regression backpropagation derivative softmaxI know that logistic regression is for binary classification and softmax regression for multi-class problem. Would it be any differences …
algorithm machine-learning classification logistic-regression softmax