đī¸ Airline Passengers Forecasting
This example demonstrates how to perform time series forecasting on the Airline Passengers dataset using the Holt-Winters method.
đī¸ Electricity Grid Drift Detection (Australia)
This example works on the Australian electricity grid dataset. The goal is to predict the class label of the grid status (binary classification) while handling concept drift in streaming data.
đī¸ Ensemble Example
This example works on the Phishing dataset. The goal is to predict whether a sample is phishing or not (binary classification) using an ensemble method. We will use AdaBoost with a Hoeffding Tree base classifier.
đī¸ Heart Failure
This example works on the Heart Failure Dataset. There are 11 clinical features for predicting heart disease events.
đī¸ Linear Models Example
This example demonstrates how to build and evaluate linear model pipelines for two different datasets: a phishing detection dataset and a Trump approval rating dataset.
đī¸ Model Selection
This example demonstrates how to perform online model selection using a multi-armed bandit approach on the Phishing dataset.
đī¸ World Happiness Report
This example demonstrates how to build and evaluate multiple regression pipelines using the World Happiness Report dataset. The goal is to predict the happiness score of a country based on various features.