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ACTU 491

Topics in Actuarial Mathematics

3 credits · Undergraduate

Winter 2026 · Statistical Learning

Topics

  • Cross-validation
  • Regression, generalized linear and generalized additive models
  • Variable selection
  • Ridge regression and LASSO
  • Classification and nearest neighbors
  • Linear and quadratic discriminants
  • Logistic regression and support vector machines
  • Tree-based methods
  • Introductory neural networks
  • Unsupervised learning
  • K-means and hierarchical clustering
  • Principal-component analysis

Readings

  • Listed textbook (requirement not stated): G. James, D. Witten, T. Hastie and R. Tibshirani. An Introduction to Statistical Learning. Springer. https://www.statlearning.com/
    Listed reading
  • Listed textbook (requirement not stated): J. Friedman, T. Hastie and R. Tibshirani. The Elements of Statistical Learning. Springer Series in Statistics. https://web.stanford.edu/~hastie/ElemStatLearn/
    Listed reading
Winter 2026 · MACF 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2026 · STAT 380

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2025 · ACTU 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2025 · MACF 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2025 · STAT 380

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2024 · ACTU 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2024 · MACF 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2024 · STAT 380

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Fall 2023 · ACTU 491

Readings

  • I. Karatzas and S. E. Shreve, Brownian Motion and Stochastic Calculus, Springer.
    Listed reading; requirement unspecified
  • B. Oksendal, Stochastic Differential Equations, Springer.
    Listed reading; requirement unspecified
Fall 2023 · MACF 491

Readings

  • I. Karatzas and S. E. Shreve, Brownian Motion and Stochastic Calculus, Springer.
    Listed reading; requirement unspecified
  • B. Oksendal, Stochastic Differential Equations, Springer.
    Listed reading; requirement unspecified
Winter 2023 · MACF 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2023 · STAT 380

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2022 · ACTU 491

Readings

  • I. Karatzas and S. E. Shreve, Brownian Motion and Stochastic Calculus, Springer.
    Listed reading; requirement unspecified
  • B. Oksendal, Stochastic Differential Equations, Springer.
    Listed reading; requirement unspecified
Winter 2022 · MACF 491

Readings

  • I. Karatzas and S. E. Shreve, Brownian Motion and Stochastic Calculus, Springer.
    Listed reading; requirement unspecified
  • B. Oksendal, Stochastic Differential Equations, Springer.
    Listed reading; requirement unspecified
Winter 2022 · MACF 491

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Winter 2022 · STAT 380

Readings

  • An introduction to statistical learning, by G. James, D Witten, T. Hastie and R. Tibshirani, Springer.
    Listed reading; requirement unspecified
  • The elements of statistical learning, by J. Friedman, T. Hastie and R. Tibshirani, Springer series in statistics.
    Listed reading; requirement unspecified
Fall 2021 · ACTU 491

Readings

  • Shapiro, A., Dentcheva, D., & Ruszczyński, A. (2014). Lectures on stochastic programming: modeling and theory. Society for Industrial and Applied Mathematics.
    Listed reading; requirement unspecified
  • Marceau, É. (2013). Modélisation et évaluation quantitative des risques en actuariat, Modèle sur une période, Springer-Verlag, France.
    Listed reading; requirement unspecified
Sources