REFERENCES

  1. Aggarwal, C. C. (2016). Recommender Systems (Vol. 1). Springer Cham.
  2. Agrawal, R., Imielinski, T., and Swami, A. (1993). Mining associations between sets of items in massive databases. In: Proceedings of the 1993 ACM‐SIGMOD International Conference on Management of Data, pp. 207–207. New York: ACM Press.
  3. Berry, M. J. A., and Linoff, G. S. (1997). Data Mining Techniques. New York: Wiley.
  4. Berry, M. J. A., and Linoff, G. S. (2000). Mastering Data Mining. New York: Wiley.
  5. Breiman, L., Friedman, J., Olshen, R., and Stone, C. (1984). Classification and Regression Trees. Boca Raton, FL: Chapman & Hall/CRC (orig. published by Wadsworth).
  6. Brin, S., Motwani, R., Ullman, J. D., and Tsur, S. (1997). Dynamic itemset counting and implication rules for market basket data. In: Proceedings of the 1997 ACM SIGMOD international conference on Management of data, pp. 255–264. New York: ACM Press.
  7. Chatfield, C. (2003). The Analysis of Time Series: An Introduction, 6th ed. Boca Raton, FL: Chapman & Hall/CRC.
  8. Delmaster, R., and Hancock, M. (2001). Data Mining Explained. Boston, MA: Digital Press.
  9. Efron, B. (1975). The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis. Journal of the American Statistical Association, vol. 70, number 352, pp. 892–892.
  10. Few, S. (2012). Show Me the Numbers, 2nd ed. Oakland, CA: Analytics Press.
  11. Few, S. (2021). Now You See It. 2nd ed. Oakland, CA: Analytics Press.
  12. Fleming, G., and Bruce, P. C. (2021). Responsible Data Science. Hoboken, ...

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