Summary of Bagging | Introduction | Part 1
The video is an introduction to bagging, a technique used in machine learning for classification problems. The speaker discusses the importance of bagging and explains the methodology step by step. The main points covered in the subtitles include:
- Introduction to bagging as a technique for improving classification
- Explanation of how bagging works and when to use it
- Discussion on creating base models and training them on different data sets
- Importance of creating variety in base models
- Types of bagging, including sampling with and without replacement
- Demonstration of the process using data sets and decision trees
Speakers/sources
- Unnamed speaker in the YouTube video
Notable Quotes
— 00:00 — « [ »
— 00:00 — « [ »
— 26:12 — « do not give all the cards, remove acidity »
— 28:17 — « you have to use random special, then what will you do sample. »
— 28:54 — « Sea turtles now do call of duty every day, its a simple thing. »
Category
Educational