A sigmoid function is a mathematical function having an "S" shape (sigmoid curve). Often, sigmoid function refers to the special case of the logistic function defined by the formula S ( t ) = 1 / (1 + e^-t)
Sigmoid function (Wikipedia)
Questions tagged [sigmoid]
256 questions
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Sigmoid scale and inverse with custom range
I'm having brain block figuring out how to scale a variable within a custom range using Sigmoid, and then to inverse that scaling.
For example, the below Python script scales variable x between 0 and top, and to then inverse that scaling.
import…
BenP
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In Caffe, Does TanHLayer Backward compute error gradient w.r.t. the sigmoid inputs?
I'm new to Caffe.
TanHLayer's Doxygen documentation says that,
Backward_cpu()
Computes the error gradient w.r.t. the sigmoid inputs.
http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1TanHLayer.html
Why does it takes sigmoid inputs, not TanH?
It…
moco
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Implementing sigmoid function in python
I am trying to implement a simple neural network for XOR function.
The activation function I am using is Sigmoid function.
The code for the sigmoid function is:
def ActivationFunction(a)
e = 2.671 # Sigmoid Function
expo =…
pr22
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Sigmoid activation for multi-class classification?
I am implementing a simple neural net from scratch, just for practice. I have got it working fine with sigmoid, tanh and ReLU activations for binary classification problems. I am now attempting to use it for multi-class, mutually exclusive problems.…
KOB
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Tensorflow custom estimator for logical 'AND'
I'm trying to create a simple one-layer/one-unit nn with tensorflow custom estimators that will be able to compute logical AND operation, but I've got a trouble with sigmoid activation -- I want to set threshold
here is my code
x = np.array([
…
deathmood
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Image Classification using Tensorflow
I am doing transfer-learning/retraining using Tensorflow Inception V3 model. I have 6 labels. A given image can be one single type only, i.e, no multiple class detection is needed. I have three queries:
Which activation function is best for my…
Pradip Gupta
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Binary features with 0,0,0, in NN always return 0.5
Let's assume we have three columns, with binary features (0,1). One row in dataset is 0,0,0 with label 0.
The problem I am facing is:
When assigning weights to this row and activating sigmoid function, I'll always receive 0.5, because an array of…
Makaroniiii
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Fitting experimental data points to different cumulative distributions using R
I am new to programming and using R software, so I would really appreciate your feedback to the current problem that I am trying to solve.
So, I have to fit a cumulative distribution with some function (two/three parameter function). This seems to…
numb
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Sigmoid function and derivative of sigmoid function in ANN
I'm making ANN from a tutorial. In the tutorial, the sigmoid and dsigmoid are as following:
sigmoid(x) = tanh(x)
dsigmoid(x) = 1-x*x
However, by definition, dsignmoid is derivative of sigmoid function, thus it should be…
Dee
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Architecture of the neural network
I was reading a paper and the authors described their network as follows:
"To train the corresponding deep network, a fully connected network with one
hidden layer is used. The network has nine binary input nodes. The hidden layer contains one…
Nima
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Sigmoid function in the neuralnet package in R
I can't seem to find any documentation of how to apply a sigmoid function in the neuralnet package, I tried:
neuralnet(...,act.fct="sigmoid")
However this returned;
Error: ''act.fct' is not known
John Meighan
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Neural network tutorial, softmax activation instead of sigmoid
I am working through an FNN tutorial, previously after researching i learnt that i will need to use softmax activation for my own ML problem rather than sigmoid as shown.
After hours of looking through tutorials i cannot find a basic example of…
Thiedent
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Sigmoid function for large numbers in Python
Im doing a Neural network task with Sigmoid activation function. My networks input is image(MNIST dataset) and because dimension of each image is 28*28, When I have to convert them to a vector, i will have N*784 matrix. Multiplication of this large…
Fcoder
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Big number of input neurons causes large weighed sum
I'm trying to create a neural network for my University project and have run into a problem. The network is to be used for image recognition for recognizing 320 x 200 pixel images. This means, that the number of input neurons in my network is 64.000…
Chraebe
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return probability for numbers [100,10000]
I want to obtain probabilities for integer numbers [100,10000]. if number is close to 100 then i want very high probabilty (around 0.99), if number is close to 10000 i want very low probabilty(around 10^-10). I use Python language. Any help is…
