Classification Problems
Explore how to handle binary classification problems by learning to assign class labels, generate synthetic datasets, and prepare data with PyTorch and Scikit-Learn. Understand the importance of splitting and standardizing data, and get ready to create and evaluate classification models using probability predictions.
We'll cover the following...
Introduction to classification problems
We will now switch to handling different classes of problems known as classification problems. In a classification problem, we are trying to predict which class a data point belongs to.
Let us say we have two classes of points; they are either red or blue. These are the labels (y) of the points. Sure enough, we need to assign numeric values to them. We could assign zero to red and one to blue. The class associated with zero is the negative class, while one corresponds to the positive class.
In a nutshell, for binary classification, we have:
| Color | Value | Class |
|---|---|---|
| Red | 0 | Negative |
| Blue | 1 | Positive |
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IMPORTANT: In ...