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7 Machine Learning
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PSY2014M: Machine LearningDr David A. Ellis
RecapOne 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!
TodayData Analysis beyond inferential statisticsQuick task, in groups I want to know a bit about what inferential tests you are familiar with.
Yogi BerraIts tough to make predictions, especially about the future
Supervised vs UnsupervisedSupervised building a model for predicting an output based on one or more inputsUnsupervised inputs but no supervising output
Wages (Supervised)
Three groups of what? (Unsupervised)
Stress over time
Types of statistical learning
Two Extremes
QuestionsI 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 ProblemsA 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 examplesPredicting first-episode psychosis by basic symptom criteria (Schultze-Lutter 2007)Predicting personality (Li et al 2014)
Predicting anxiety from personality
RememberThere 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.
ReferencesJames, 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., Baszkiewicz, 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., Klosterktter, J., Picker, H., Steinmeyer, E. M., & Ruhrmann, S. (2007). Predicting first-episode psychosis by basic symptom criteria. Clin Neuropsychiatry, 4(1), 11-22.
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