Classify vs. Predict
Explore the distinction between classifiers and predictors within neural networks. Understand how linear functions can separate data groups for classification tasks and how models learn to improve these separations. This lesson helps you grasp foundational concepts essential for building and optimizing neural network models.
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The difference between a classifier and a predictor
The model we built in the previous lesson is called a predictor because it takes an input and makes a prediction about what the output should be. We refined that prediction by adjusting an internal parameter, informed by the errors we saw when comparing the answers with a true example. Now, let’s look at the following graph, showing the widths and lengths of garden bugs.
We can clearly see two groups. The caterpillars are thin and long, and the ladybugs are wide and short.
Remember the predictor that ...