AIF-C01 Question 3

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A1

  Decision Trees can handle multi-class classification problems, making them suitable for categorizing genes into 20 distinct classes

• Chose A2

  Linear regression produces continuous numerical outputs, and logistic regression outputs probabilities. Because the requirement is to explain the decision logic through clear rules, a (A) decision tree is the most suitable choice, unlike neural networks which lack interpretability.

• Chose A13

  Decision trees provide a transparent and interpretable model. They allow you to understand how decisions are made by following the path of splits at each node, which directly shows the influence of input features (gene characteristics) on the final output (gene category). This helps document and explain how the model arrives at its classifications, satisfying the requirement for transparency regarding the inner mechanism of the model.