3.5.1. Supervised Classification

Try these first

1. 1.

   What is supervised classification?

   Hint

   Think about how a teacher helps students learn.

2. 2.

   Name one algorithm used in supervised classification.

   Hint

   Consider what you've learned about probabilities.

3. 3.

   What does supervised classification require?

   • Unlabeled data
   • User-defined training data
   • Random samples

   Hint

   Consider how you might train a model to recognize objects.

4. 4.

   True or False: Support Vector Machines use multiple decision trees to classify data.

   • True
   • False

   Hint

   Think about how SVM relates to different classes.

5. 5.

   Given an unknown dataset of satellite images, describe how you would go about applying supervised classification. What steps would you take?

   Hint

   Consider starting with labeling your known data.

6. 6.

   Evaluate the impact of quality training data on the success of supervised classification. What might happen if the training data is biased?

   Hint

   Reflect on how student biases affect assessment results.