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Summary Mastering Decision Trees: From Fundamentals to Advanced Applications $7.99   Add to cart
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Summary Mastering Decision Trees: From Fundamentals to Advanced Applications
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  • Course
  • Machine Learning
  • Institution
  • Machine Learning

Unlock the power of decision trees with this in-depth course designed to take you from the basics to advanced techniques. Decision trees are one of the most intuitive and versatile machine learning algorithms, widely used for both classification and regression tasks. This course is ideal for beginn...

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Document information

  • August 7, 2024
  • 3
  • 2024/2025
  • Summary

Subjects

  • decision tree

Written for

  • Machine Learning
All documents for this subject (77)

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reetusharma

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Decision Trees: How to Make Predictions using Decision Trees
Decision trees are a type of supervised learning algorithm used for both
classification and regression tasks. They work by recursively splitting the data
into subsets based on the most significant attributes until a stopping criterion
is met. Here's how to make predictions using decision trees:




Data Preparation

.
 Prepare the dataset by cleaning, transforming, and normalizing
the data.
 Split the dataset into training and testing sets.
.
Feature Selection

.

 Choose the features that will be used to split the data.
 Measure the quality of a split using metrics such as information
gain or Gini impurity.

.
Tree Growth

.

 Grow the tree by recursively splitting the data until a stopping
criterion is met.

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