Demonstrates how to use ML.NET and Oxyplot to implement some Machine Learning use cases in an MVVM UWP app. Currently works against ML.NET v1.3.1 and is tested against v1.4.0-preview.
If you want to see these same ML.NET scenarios in Jupyter Notebooks and XPlot, then visit https://github.com/XamlBrewer/ML.NET-Jupyter-Notebooks.
The UWP app demonstrates the following Machine Learning scenarios:
- Clustering
- Multiclass Classification
- Binary Classification
- Regression
- Feature Contribution Calculation
- Permutation Feature Importance Calculation
- Recommendation
- Recommendation using Field-Aware Factorization Machine
- Automated model generation with AutoML
- Feature Distribution Analysis with Boxplot Diagrams
- Feature Correlation Analysis with Heatmap Diagrams
