Data Mining & Business Intelligence - Data Mining & Business Intelligence | Tutorial #27 | Decision Trees (Solved Problem)

Master the Art of Data Mining and Business Intelligence: Unlock Insights, Drive Decisions, and Transform Data into Actionable Knowledge with RANJI RAJ's Comprehensive Tutorials!

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16 learners

What you'll learn

Understand the KDD process and its role in data mining.
Apply data integration and transformation techniques for data preparation.
Implement various data reduction strategies to optimize data handling.
Explore diverse classification and clustering algorithms for effective data analysis.

This course includes

5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Data Mining & Business Intelligence DMBI Solving using decision trees in data mining Gain entropy SWM ML decision tree clustering python decision tree clustering r difference between clustering and decision tree unsupervised decision tree in r clustering tree in machine learning

Full Transcript

A decision tree is a structure that includes a root node, branches, and leaf nodes. Each internal node denotes a test on an attribute, each branch denotes the outcome of a test, and each leaf node holds a class label. The topmost node in the tree is the root node. In this video, we will solve a problem on Decision Trees #DataMining #DecisionTrees Follow me on Instagram 👉 https://www.instagram.com/ngnieredteacher/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj

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