Machine learning models can be classified into the following three types based on the task performed and the nature of the output:
- Regression: The output variable to be predicted is a continuous variable, e.g., the score of a student on a subject.
- Classification: The output variable to be predicted is a categorical variable, e.g., classifying incoming emails as spam or ham.
- Clustering: No predefined notion of a label is allocated to the groups/clusters formed, e.g., customer segmentation.
you can classify machine learning models into two broad categories:
- Supervised learning methods
- Past data with labels is used for building the model.
- Regression and classification algorithms fall under this category.
- Unsupervised learning methods
- No predefined labels are assigned to past data.
- Clustering algorithms fall under this category.