Data Mining Using Orange and Python
Mitchell Smith, Chief Software Architect, Array BioPharma
Date: Wednesday, July 26
Time: 5:20pm - 6:05pm
- How to create predictive models in Orange such as naive bayes, k-Nearest Neighbors, support vector machines, logistic regression, classification trees with boosting or bagging, etc.
- How to utilize model validation techniques such as cross-validation, random sampling, etc.
- Model preprocessing such as filters, feature subset selection, data categorization, etc.
- How to create your own learners and classifiers
- Loading data from tab-delimited and C4.5 files
Real world examples will be taken from data mining work in the pharmaceutical domain. A basic knowledge of data mining techniques is assumed.