Building a model for classification
In this recipe, we will perform another type of analysis: classification. Classification analysis within the context of data frame analytics in the Elastic Stack is a powerful ML technique used to categorize data into predefined classes or groups.
This process involves training a model on a dataset with known class labels, thereby enabling the model to learn how to categorize new, unseen data. In the Elastic Stack, classification is commonly applied to tasks such as spam detection, customer segmentation, and sentiment analysis.
In this recipe, we will train a model to classify traffic according to the free-flow, heavy, congested, and unknown categories using the Rennes traffic dataset, based on features such as location, hour of the day, day of the week, and maximum authorized speed.
Getting ready
Make sure you have worked through the following recipes:
- Exploring your data in Discover in Chapter 6
- Building a model to perform...
