Python Programming

In scikit-learn, the classification pipeline is exactly the same:

• Arrange data into $\mathbf{X}$ and $\mathbf{y}$
• Choose your model
• Initialise your model with some hyperparameters
• Fit your model to $\mathbf{X}$ and $\mathbf{y}$
• Predict labels $\hat{\mathbf{y}}^{test}$ for $\mathbf{X}^{test}$
• Evaluate the model performance by comparing $\hat{\mathbf{y}}^{test}$ against $\mathbf{y}^{test}$

I will take you through the whole pipeline. Step by step, we will discuss how to apply scikit-learn to a classification problem.