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Why Decision Tree is called Decision Tree? 🌲🎄 Explained in 60 Seconds
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Decision tree algorithms are popular in machine learning and data analysis due to their simplicity, interpretability, and effectiveness. Decision trees mimic human decision-making processes. They consist of nodes, branches, and leaves, where nodes represent decisions, branches represent possible outcomes, and leaves represent final predictions.
It was named so because of its Botanical Inspiration. The term "decision tree" was inspired by its visual resemblance to an upside-down tree, with branches representing decisions and leaves as final outcomes.
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It was named so because of its Botanical Inspiration. The term "decision tree" was inspired by its visual resemblance to an upside-down tree, with branches representing decisions and leaves as final outcomes.
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👉 Become a Data Scientist, coming from any background, even without leaving your job!
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