Network Architecture
Problem Type
ⓘ
Choose the type of problem for the neural network to solve
Spiral Classification
Circle Classification
Hidden Layers
ⓘ
Number of layers between input and output
Neurons per Layer
Number of neurons in each hidden layer
Training Parameters
Learning Rate
ⓘ
Speed of learning (smaller = more stable but slower)
Activation Function
ⓘ
Function used to determine neuron activation
Tanh
Sigmoid
ReLU
Controls
Start Training
Reset Network
Pause
Epoch:
0
Error:
0.000
Accuracy:
0%
Neural Network Structure
Neurons
Positive Weights
Negative Weights
Classification Results
Class 1 (Output > 0.5)
Class 0 (Output ≤ 0.5)