• Home
  • Recent Q&A
  • Java
  • Cloud
  • JavaScript
  • Python
  • SQL
  • PHP
  • HTML
  • C++
  • Data Science
  • DBMS
  • Devops
  • Hadoop
  • Machine Learning
in Data Science by
Q:
Describe in brief any type of Ensemble Learning?

1 Answer

0 votes
by

Ensemble learning has many types but two more popular ensemble learning techniques are mentioned below.

Bagging

Bagging tries to implement similar learners on small sample populations and then takes a mean of all the predictions. In generalised bagging, you can use different learners on different population. As you expect this helps us to reduce the variance error.

 

Boosting

Boosting is an iterative technique which adjusts the weight of an observation based on the last classification. If an observation was classified incorrectly, it tries to increase the weight of this observation and vice versa. Boosting in general decreases the bias error and builds strong predictive models. However, they may over fit on the training data.

Related questions

+1 vote
asked Jan 6 in Structured Data Classification by sharadyadav1986
+1 vote
asked Aug 8, 2020 in DevOps by sharadyadav1986
...