Causal Data Mining

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Causal Data Mining
Richard Scheines Dept. of Philosophy, Machine
Learning, Human-Computer Interaction
Carnegie Mellon
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1. Predictive Data Mining

• Finding predictive relationships in data
• What feature of student behavior predicts
  learning
• Who will default on credit cards
• Who will get an A in your course
• Which HS students will do well at CMU
• Do students cluster by learning style

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Causal Data Mining

• Finding causal relationships in data
• What feature of student behavior causes learning
• What will happen when we make everyone take a
  reading quiz before each class
• What will happen when we program our tutor to
  intervene to give hints after an error

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Predictive Data Mining
Data Mining Search
Predictive Model Y f(X1, X2, Xk)
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Predictive Data Mining

• Model Classes
• Simple Regression
• Locally Weighted Regression
• Logistic Regression
• Neural Nets
• Vector Support Machines
• Decision Trees
• Bayes Net
• Naïve Bayes Classifier
• Independent Components
• Clustering
• Etc.

Data Mining Search
Predictive Model Y f(X1, X2, Xk)
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Predictive Data Mining
Data Mining Search
Predictive Model under Constraints Y f(X1, X2,
Xk), e.g., f ? Additive functions
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Predictive Data Mining
Data Mining Search
Predictive Model under Constraints Y f(X1, X2,
Xk), Or Probability Model under
Constraints P(Y X1, X2, , Xk), where P ?
Gaussian, with mean 0
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Predictive Data Mining
Decision Tree Search
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Predictive Data Mining ?Causal Data Mining
Conditioning is not the same as intervening

• P(Y X1, X2, , Xk)
• ?
• P(Y X1set, X2, , Xk)

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Causal DiscoveryStatistical Data ? Causal
Structure
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Causal Discovery Software TETRAD IV
www.phil.cmu.edu/projects/tetrad
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Full Semester Online Course in Causal
Statistical Reasoning
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Full Semester Online Course in Causal
Statistical Reasoning

• Course is tooled to record certain events
• Logins, page requests, print requests, quiz
  attempts, quiz scores, voluntary exercises
  attempted, etc.
• Each event was associated with attributes
• Time
• student-id
• Session-id

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Printing and Voluntary Comprehension Checks 2002
--gt 2003
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References

• Causation, Prediction, and Search, 2nd Edition,
  (2000), by P. Spirtes, C. Glymour, and R.
  Scheines ( MIT Press)
• Causality Models, Reasoning, and Inference,
  (2000), Judea Pearl, Cambridge Univ. Press
• Shih, B., Koedinger, K., Scheines, R. (2008).
  A Response Time Model for Bottom-Out Hints as
  Worked Examples. Proceedings of the First
  Educational Data Mining Conference.
• Shih, B., Koedinger, K., and Scheines, R. (2007)
  "Optimizing Student Models for Causality." in
  Proceedings of the 13th International Conference
  on Artificial Intelligence in Education.
• Arnold, A., Beck, J., and Scheines, R. (2006).
  "Feature Discovery in the Context of Educational
  Data Mining An Inductive Approach." Proceedings
  of the AAAI2006 Workshop on Educational Data
  Mining, Boston, MA.
• Scheines, R., Leinhardt, G., Smith, J., and Cho,
  K. (2005) "Replacing Lecture with Web-Based
  Course Materials, Journal of Educational
  Computing Research, 32, 1, 1-26.