Getting Started with Classification in Machine Learning

Classification is a supervised machine learning technique used to predict labels or categories from input data. It assigns each data point to a predefined class based on learned patterns.

• Predict categories: Determines the class of new data points.
• Uses labeled data: Trained on datasets where the correct class is known.
• Common examples: Spam vs non spam emails, diseased vs. healthy patients.

For example: A classification model might be trained on dataset of images labeled as either dogs or cats and it can be used to predict the class of new and unseen images as dogs or cats based on their features such as colour, texture or shape.

Types of Classification

Classification in machine learning involves sorting data into categories based on their features or characteristics. The type of classification problem depends on how many classes exist and how the categories are structured.