What term refers to the process of assigning inputs to predefined classes or categories?

What term refers to the process of assigning inputs to predefined classes or categories?

• A. Regression
• B. Classification
• C. Clustering
• D. Normalization

Answer: (B)

The process of assigning inputs to predefined classes or categories is known as classification. This technique is fundamental in supervised machine learning, where the goal is to train a model on labeled data so that it can predict the class or category for new, unseen inputs based on the patterns learned during training. In classification, each input is analyzed based on its features and assigned to one of the predefined classes. For example, an email can be classified as "spam" or "not spam" based on its content and characteristics. The model uses algorithms, such as decision trees, support vector machines, or neural networks, depending on the complexity and nature of the data. In contrast, regression refers to predicting a continuous output rather than a category, clustering involves grouping similar data points without predefined categories, and normalization is a data preprocessing step aimed at adjusting the scale of features but doesn't classify data into categories. Understanding these distinctions is vital for effectively applying the appropriate techniques in various AI applications.

The process of assigning inputs to predefined classes or categories is known as classification. This technique is fundamental in supervised machine learning, where the goal is to train a model on labeled data so that it can predict the class or category for new, unseen inputs based on the patterns learned during training.

In classification, each input is analyzed based on its features and assigned to one of the predefined classes. For example, an email can be classified as "spam" or "not spam" based on its content and characteristics. The model uses algorithms, such as decision trees, support vector machines, or neural networks, depending on the complexity and nature of the data.

In contrast, regression refers to predicting a continuous output rather than a category, clustering involves grouping similar data points without predefined categories, and normalization is a data preprocessing step aimed at adjusting the scale of features but doesn't classify data into categories. Understanding these distinctions is vital for effectively applying the appropriate techniques in various AI applications.