Provide reasons for preferring one machine learning model over another. There are two main ways to classify things: K-nearest neighbor (a), looking back (c), and learning more (d) are all examples of this.?

Use examples to justify your machine learning model choice. Two novel ways to categorise things include the K-nearest neighbour, looking backward, and gathering supplementary information.

Four different machine learning algorithms are shown in this section, which may be used for supervised learning on a given dataset. Give a description of any four variables you may use to help you choose which one to utilize to determine whether or not a tumor is malignant.

Show the difference in the interaction of rules, data and answers in machine learning and classical programming.