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Simpler Binary Classification Tasks Usually Need Fewer Labeled Examples
For binary classification tasks, an easier task generally requires fewer labeled training examples than a harder task to reach a comparable performance level. Here, task difficulty is an informal comparison rather than a precisely defined quantity.
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Informal View of Task Difficulty in Neural Networks
Which binary classification task is likely the easiest and needs the fewest training examples?
True or False: A simpler binary classification problem usually needs fewer labeled examples than a more difficult one.
Simpler tasks need less data
Match each vision task to its relative difficulty rank in the ordered list (1 = easiest, 5 = hardest).
Order these five classification tasks from easiest (1) to hardest (5).
How does task difficulty influence data needs when dividing a pipeline into subtasks?
A model that must distinguish two very similar bird species usually needs less training data than a model that only decides whether a photo is indoors or outdoors.
Binary Output in Several Toy Image Tasks
Match each image task description to the difficulty category it best fits.
Put the task-formulation steps in a sensible order when choosing a component for a text-classification pipeline.
How Task Difficulty Affects Training Data Needs
Choosing the Easier Image Classification Task
Why Some Classification Tasks Need Less Training Data
Choose Pipeline Components That Can Be Learned from Limited Data