Decision Tree Algorithm Tutorial | Decision Tree Machine Learning | Decision Tree Example
Decision Tree Algorithm Tutorial | Decision Tree Machine Learning | Machine Learning Tutorial
A decision tree is one of the most commonly used algorithms to solve real-world problems, and it's considered a standard management tool.
Decision Tree is used in engineering, law, business, and various other domains.
Decision tree is used both for classification as well as regression problems. However, it's mainly used for classification purposes. Decision tree algorithms capture non-linearity and are used for situations where low bias is preferable with tolerance for high variances, such as segmentation.
DT can be used for binary classification and multiclass classification as well. There is no need to know hi-fi statistics or mathematics to implement a decision tree. So what are we waiting for? Let's dive into the course.
#decisiontree #machinelearning
🔹 Agenda:
Decision tree learning and its type and its differences
Splitting criteria of the decision tree, Finding rightly sized tree
Decision tree case study
Misclassification of the error, entropy, and probability
🔹 Topics Covered:
0:00:00 - Introduction to decision tree
0:01:35 - What is decision tree learning and its types
0:04:19 - Classification tree learning and important terms
0:13:09 - Difference between tree model and logistic regression model
0:21:10 - Decision Tree Case Study: Gold loan attrition problem
0:50:05 - Career Fields in Analytics
1:07:34 - Gini index, entropy,
1:09:43 - Decision tree algorithms
1:10:29 - Advantages and disadvantages of decision tree
1:22:45 - Decision tree example
1:56:02 - Summary
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