_____________are machine learning algorithms that first build a model from the training dataset before making any predictions on future datasetsLazy learnersInstance based learnersEager learnersmedium learners

To answer the question, we need to understand the different types of machine learning algorithms mentioned in the given options: lazy learners, instance-based learners, eager learners, and medium learners.

1. Lazy learners: These are machine learning algorithms that do not build a model from the training dataset. Instead, they store the training dataset and make predictions by comparing new instances to the stored instances. Lazy learners do not perform any computation until a prediction is required.

2. Instance-based learners: Instance-based learners are similar to lazy learners in that they store the training dataset. However, they use a similarity measure to find the most similar instances in the training dataset and make predictions based on those instances.

3. Eager learners: Eager learners, also known as eager classifiers, are machine learning algorithms that build a model from the training dataset before making any predictions. They eagerly analyze the training data and construct a generalization model that can be used to make predictions on new instances.

4. Medium learners: The term "medium learners" is not a commonly used term in machine learning. It is possible that it refers to a type of machine learning algorithm that falls between lazy learners and eager learners in terms of their approach to building models and making predictions. However, without further context or clarification, it is difficult to provide a specific explanation for medium learners.

In summary, lazy learners do not build a model, instance-based learners use stored instances for predictions, eager learners build a model before making predictions, and the term "medium learners" requires further clarification.