What type of data is used in supervised learning?

What type of data is used in supervised learning?

• A. Unlabeled data
• B. Mixed data
• C. Labeled data
• D. Raw data

Answer: (C)

In supervised learning, the focus is on utilizing labeled data to train algorithms. Labeled data consists of input-output pairs, where each input has a corresponding output that serves as a reference for the model. This allows the algorithm to learn patterns and relationships within the data, enabling it to make predictions or classifications on new, unseen data based on what it has learned during training. The presence of labels is crucial because they provide the necessary context for the algorithm to understand the desired output. When the model encounters new input, it uses the patterns it has learned from the labeled data to predict the corresponding output accurately. Thus, the ability to train a model effectively in supervised learning hinges significantly on the availability and quality of labeled data.

In supervised learning, the focus is on utilizing labeled data to train algorithms. Labeled data consists of input-output pairs, where each input has a corresponding output that serves as a reference for the model. This allows the algorithm to learn patterns and relationships within the data, enabling it to make predictions or classifications on new, unseen data based on what it has learned during training.

The presence of labels is crucial because they provide the necessary context for the algorithm to understand the desired output. When the model encounters new input, it uses the patterns it has learned from the labeled data to predict the corresponding output accurately. Thus, the ability to train a model effectively in supervised learning hinges significantly on the availability and quality of labeled data.