Softmax Layer
This function block implements the Softmax activation function commonly used in machine learning, particularly in multi-class classification problems. It outputs probabilities for each class based on the input data.
π₯ Inputs
This function block does not have any inputs as it functions as a layer in a neural network.
π€ Outputs
This function block does not produce any direct outputs but serves as a layer for downstream layers that will utilize its probabilities for further processing.
πΉοΈ Controls
Axis
A dropdown selection to determine the axis along which the Softmax function will be computed.
Select
1
for applying the Softmax across the rows.Select
-1
for applying the Softmax across the columns.
π¨ Features
Multi-Class Capability
Allows the softmax activation to be computed across specified axes for multi-class predictions.
Simple Configuration
The axis selection is straightforward, facilitating easy model configuration for users.
π Usage Instructions
Select Axis: Use the dropdown menu to choose the axis for the Softmax function (either
1
or-1
).Integrate into Model: Once configured, this block can be integrated into a neural network model where softmax probabilities are required.
π Evaluation
When utilized within a neural network model, this block will process inputs and provide softmax probabilities, thereby aiding in classification tasks.
π‘ Tips and Tricks
π οΈ Troubleshooting
Last updated
Was this helpful?