TimeSeriesPredictionsPlot

Assesses the model’s accuracy in predicting time series data by comparing actual versus predicted values through visual plots.

Purpose

The purpose of this function is to visualize the actual versus predicted values for time series data across different models, aiding in the assessment of model performance.

Test Mechanism

The function iterates through each dataset-model pair, plots the actual values from the dataset, and overlays the predicted values from each model using Plotly for interactive visualization. This enables a direct visual comparison between the models’ performance.

Signs of High Risk

• Large discrepancies between actual and predicted values indicate poor model performance.
• Systematic deviations in predicted values can highlight model bias or issues with data patterns.

Strengths

• Provides a clear visual comparison of model predictions against actual values.
• Uses Plotly for interactive and visually appealing plots.
• Can handle multiple models and datasets, displaying them with distinct colors.

Limitations

• Assumes that the dataset is provided as a DataFrameDataset object with a datetime index.
• Requires that dataset.y_pred(model) returns the predicted values for the model.
• Visualization might become cluttered with a large number of models or datasets.