Mid‑Level Test of Core ML Algorithms
Test your knowledge of core machine learning algorithms with eight challenging items.
Quiz Questions
Answer all questions below and test your knowledge.
- 1
Which algorithm iteratively updates parameters to minimize a differentiable loss using the steepest slope?
- 2
In a decision tree, which impurity measure calculates the probability that a randomly chosen element would be incorrectly labeled if it were randomly labeled according to the distribution of labels in the node?
- 3
Which clustering technique partitions data by assigning points to the nearest of a predetermined number of centroids and then recomputes centroids until convergence?
- 4
Which supervised method constructs a hyperplane that maximizes the margin between two classes in a high‑dimensional feature space?
- 5
Which algorithm builds an ensemble by training successive learners on the residual errors of the previous model?
- 6
Which method estimates the probability of a class by applying Bayes’ theorem assuming feature independence?
- 7
Which neural architecture processes data sequentially, maintaining a hidden state that captures information from previous time steps?
- 8
Which dimensionality reduction technique projects data onto orthogonal axes that capture the greatest variance?
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