Learn Before
Sample Calculation of Softmax Output Layer
Say we have .
Then, .
We sum the entries in to yield the denominator of the activation: $7.39 + 0.37 + 20.1 + 1096.6 = 1124.5$.
Finally, normalize the probabilities by dividing each entry in by the summation we just computed:
0
1
Tags
Data Science
Related
Sample Calculation of Softmax Output Layer
Example of a SoftMax activation transformation
Maximum Probability Decision Rule
Consider a 4-class classification problem where the final layer of a model produces the following pre-activation scores for a single input:
[1.0, 2.0, 1.5, 5.0]. The model then uses an activation function that exponentiates each score and normalizes the results to produce a probability distribution. Without performing the full calculation, which of the following statements best describes the resulting probability distribution?Calculating an Output Probability
Classifier Output Analysis
Computational Cost of Fully Connected Layers