Today’s class was quite engaging, featuring discussions about classmates’ projects and ideas. Later, we delved into a class focused on Decision Trees.

The Decision Tree algorithm functions by categorizing data, such as a set of animal traits, to identify a specific animal based on those characteristics. It begins by posing a question, like “Can the animal fly?” This question divides the animals into groups based on their responses, guiding the progression down the tree.

With each subsequent question, the tree further refines the groups, narrowing down the possibilities until it arrives at a conclusion regarding the identity of the animal in question. Trained using known data, the decision tree learns optimal inquiries (or data divisions) to efficiently arrive at accurate conclusions. Consequently, when presented with unfamiliar data, it applies its learned patterns to predict the identity of the animal.

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