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Tutorials

Jupyter Notebooks for tutorials of scores.

Firstly run Data Fetching to fetch the data needed for some later notebooks

Data Fetching

Continuous

Additive Bias, Multiplicative Bias and Percent Bias

MAE

RMSE

MSE

Nash–Sutcliffe Model Efficiency Coefficient (NSE)

Pearson's Correlation

Kling-Gupta Efficiency

Quantile Loss

Murphy Diagrams

Flip-Flop Index

Consistent Scores

Threshold Weighted Scores

Quantile Interval Score and Interval Score

Probability

Brier Score

CRPS for forecasts expressed as CDFs

CRPS for ensemble forecasts

twCRPS for ensemble forecasts

Receiver Operating Characteristic (ROC)

Categorical

Binary (Categorical/Contingency/Confusion Matrix) Scores

FIRM

SEEPS

Spatial

Fractions Skill Score

Statistical Tests

Diebold Mariano

Processing

Isotonic Regression and Reliability Diagrams

Block Bootstrapping

Emerging

Risk Matrix Score

Other

Dimension Handling

Weighting Results

Angular Data

Introduction to Pandas API