Decision Tree Learning

Decision Tree Learning is one of the most widely used and practical methods for inductive inference. Decision tree learning is one of the most successful techniques for supervised classification learning.

Decision Tree Learning Algorithms:

  1. ID3
  2. ASSISTANT
  3. C4.5

When to use Decision Tree Learning:

  • Instances are represented by attribute-value pairs
  • The Target function has discrete output values
  • Disjunctive descriptions may be required
  • The training data may contain errors
  • The training data may contain missing attribute values
Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s