Extracting (ranked) softmax values for each validation image
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Hi everyone,
I trained a model (fine tuning) to classify 10 types of images. I was just wondering if there was a simple way to return, say, a matrix containing all validation images (with their respective names/labels) and their predictive scores (classification confidence) ?
Thank you !
Best regards.
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Srivardhan Gadila
2020-8-23
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Use the activations function to get the output of softmaxLayer & use the max function to get the maximum of all scores i.e., score of the predicted class. Also I think you can use the same Name-Value Pair Arguments & Syntax used for predict function. You can refer to Visualize Activations of a Convolutional Neural Network for more examples on the usage of activations function.
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