User Guide¶
Welcome to the k-diagram User Guide!
While the Quick Start provides a fast runnable example and the Gallery showcases the various plots, this guide aims to provide a deeper understanding of the concepts behind the different visualizations and helper functions offered by k-diagram.
Here, you’ll find explanations of:
What each plot or utility does.
Why specific polar representations or data structures are used.
How to interpret the patterns and features within each diagram.
When to use specific plots and utilities for effective model evaluation, uncertainty analysis, and data preparation.
Dive into the topics below to learn more about interpreting and applying k-diagram’s specialized tools to gain richer insights from your forecasting models and data.
Guide Topics:
- Visualizing Forecast Uncertainty
- Visualizing Forecast Errors
- Evaluating Probabilistic Forecasts
- Model Comparison Visualization
- Visualizing Relationships
- Feature Importance Visualization
- Evaluating Classification Models
- Diagnosing Forecast Anomalies
- Spatial Diagnostic Plots
- Taylor Diagrams
- Contextual Diagnostic Plots
- Visualizing 1D Distributions
- Specialized Forecasting Metrics
- Forecast Utilities
- Working with Quantile Data
- Mathematical Utilities
- Datasets
- Case Study: Zhongshan Land Subsidence Uncertainty
We hope this guide enhances your ability to leverage k-diagram for comprehensive forecast analysis. For detailed function parameters, please refer to the API Reference.