Training and testing
5 important questions on Training and testing
Rule of thumb for training
What is overfitting of a classifier in the process of training a supervised learning algorithm? What does this say about the quality of the classifier?
Why should negative data come from the same domain as the positive data?
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What are hyperparameters? How can they be optimized?
What are the three steps of testing a supervised binary classifier algorithm?
- Extract the image descriptors of the images of the validation data set.
- Evaluate/Retrieve the labeling of the resulting images.
- Compare against the correct labels and obtain the accuracy
The question on the page originate from the summary of the following study material:
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