PSY2014M: Machine Learning

Dr David A. Ellis

Recap

• One of the quickest ways to critique a piece of research in psychology is to consider the statistical analysis.

• However, while it is important to know what job is performed by each cog, it is not necessary to have the skills to construct the machine inside the box!

Today

• Data Analysis – beyond inferential statistics• Quick task, in groups I want to know a bit about

what inferential tests you are familiar with.

Yogi Berra

• ‘It’s tough to make predictions, especially about the future’

Supervised vs Unsupervised

• Supervised – building a model for predicting an output based on one or more inputs

• Unsupervised – inputs but no supervising output

Wages (Supervised)

Three groups of what? (Unsupervised)

Stress over time…

Types of statistical learning

Two Extremes

Questions

• I want you to think of some real-life applications for statistical learning

• (a) Describe three real-life applications in which classification might be useful. Consider the response as well as the predictors

• (b) Describe three real-life applications in which regression might be useful. Consider the response as well as the predictors

• (c) Describe three real-life applications where cluster analysis might be useful

Regression

Classification Problems

• A patient presents a set of symptoms that could be attributes to one of three mental health complaints. Which of the three conditions does the individual have?

• On the basis of DNA sequence data for a number of patients with and without a given disease, a biologist would to figure out which DNA mutations are disease-causing and which are not.

Remember the watches?

So can we predict watch wearing based on personality

Other examples

• Predicting first-episode psychosis by basic symptom criteria (Schultze-Lutter 2007)

• Predicting personality (Li et al 2014)

Predicting anxiety from personality

Remember

• There will be no question in the exam specifically on machine learning or statistics.

• However, you will be able to include it as part of other answers.

References

• James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (p. 6). New York: Springer.

• Li, L., Li, A., Hao, B., Guan, Z., & Zhu, T. (2014). Predicting Active Users' Personality Based on Micro-Blogging Behaviors. PLOS ONE, 9(1), e84997.

• Markowetz, A., Błaszkiewicz, K., Montag, C., Switala, C., & Schlaepfer, T. E. (2014). Psycho-Informatics: Big data shaping modern psychometrics. Medical hypotheses, 82(4), 405-411.

• Schultze-Lutter, F., Klosterkötter, J., Picker, H., Steinmeyer, E. M., & Ruhrmann, S. (2007). Predicting first-episode psychosis by basic symptom criteria. Clin Neuropsychiatry, 4(1), 11-22.