Actuarium

SOA ATPAAdvanced Topics in Predictive Analytics

Associateship (ASA)
Multi-hour assessment·Project-based·120 study hours
Score 0/0 · 6 MC
  1. ATPA · Q1
    Multiple choice
    Unsupervised learning & feature engineering

    Before running k-means on variables with very different scales (e.g., premium in dollars and age in years), the analyst should:

  2. ATPA · Q2
    Multiple choice
    Unsupervised learning & feature engineering

    In a scree plot of PCA eigenvalues, the recommended number of components to retain by the 'elbow' rule is the point where:

  3. ATPA · Q3
    Multiple choice
    Unsupervised learning & feature engineering

    A clustered point has average within-cluster distance ai=2a_i=2 and average distance to the nearest other cluster bi=5b_i=5. Calculate its silhouette coefficient.

  4. ATPA · Q4
    Written answer
    Unsupervised learning & feature engineering

    A categorical rating variable (vehicle make/model) has over 500 levels. Explain the risk of using simple target-mean encoding for this variable and propose a safer alternative.

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