All Questions
6 questions
0votes
2answers
217views
Activation and Loss Function not chosen correctly when use Neural Network
I have three classes for my text dataset before. These are my classes: 0 = Cat 1 = Not Both 2 = Dog Then I use this code: ...
- 13
0votes
1answer
231views
How to deal with ternary Output neurons in the Output classification layer of a simple feedforward Neural Net?
I was looking into the multi-label classification on the output layer of a Neural Network. I have 5 Output Neurons where each Neuron can be 1, 0, or -1. independent of other Neurons. So for example an ...
1vote
0answers
27views
How does one use activation function with greater than [-1;1] range for binary classification?
In Efficient Backprop (http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf), Lecun and others propose to use activation function that don't reach target values on their asypmptotes. They explain (§ 4....
- 2,613
1vote
1answer
166views
Confusion regarding the Working mechanism of Activation function
For binary classification irrespective of the model used, the sigmoid function is a good choice for output layer because the actual output value ‘Y’ is either 0 or 1 so it makes sense for predicted ...
- 541
1vote
1answer
7kviews
Why is the softmax function often used as activation function of output layer in classification neural networks?
What special characteristics of the softmax function makes it a favourite choice as activation function in output layer of classification neural networks?
- 1,455
3votes
2answers
164views
Is classifier able to say there's no-such-case?
I am a starter in ML and I need some help... The problem Assume that I have a classifier which can classify left hand / right hand well. I am curious whether it can decide whether there's a hand in ...
