KNIME is hosting the following one-day course during the KNIME Spring Summit in Berlin on March 6, 2018:
The Power of Random: Using Perturbation Experiments to Improve Model Accuracy and Interpretation
Predictive modelers often start learning how to build models with linear methods and statistical models. These approaches usually assume smaller data, known distributions, no missing values, and more, and as a result, make building and assessing the models straightforward, blessed with many very good metrics to use to judge model accuracy and the influence of individual predictor variables. As we build models using non-parametric, highly nonlinear techniques, many of these measures no longer make sense or are impossible to apply.
This workshop summarizes a half dozen ways to use randomization in the model building process. For each, principles describing the approach will be provided, followed by demonstrations of the techniques using KNIME.
This course is intended for Data Scientists, Statisticians, Mathematicians, Computer Scientists, and IT Professionals who build and interpret predictive models. Prior predictive modeling experience is very helpful.
- Randomization principles for Sampling
- Randomization for Missing Value Imputation
- Randomization in building models (Random Forests)
- Randomization to Assess Confidence in Model Accuracy: Target Shuffling
- Randomization to Assess Variable Importance: Input Shuffling
- Randomization to Create Model Prediction Confidence Intervals
- KNIME Analytics Platform for Beginners: From installation to utilization and everything in between: March 5, 2018
- Text Mining Course for KNIME Analytics Platform: March 5, 2018
- KNIME Big Data Extensions: Data Mining with Apache Hive and Apache Spark: March 5, 2018
- Advanced Analytics Methods with KNIME Analytics Platform: March 5, 2018
- Advanced Users in KNIME Analytics Platform: Beyond the Basics: March 6, 2018
- Text Mining with KNIME Analytics Platform: Using the Textprocessing Extension: March 6, 2018
- KNIME Big Data Extensions: Data Mining with Apache Hive and Apache Spark: March 6, 2018
- IoT Analytics with KNIME Analytics Platform: Methodologies and Algorithms: March 6, 2018
See KNIME Spring Summit event page for details.