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• Leaf Node: A node that does not split further.
• Parent Node: A node that is a level above a sub-node.
• Child Node: A sub-node that falls under another node.
Let us understand about decision trees with the help of an example.
Extracurricular Activities
Yes No
Musical Theatre Self Defence Coaching Tuition
Karate
Vocals Dance
Weight Lifting
Theatre
Following are some of the important points to consider while designing a decision tree:
• There can be a possibility of multiple decision trees which lead to correct prediction for a single dataset. The
simplest one should be chosen.
• The dataset might contain redundant data at times, which does not have any reference while creating a decision
tree. Therefore, it is necessary that only those parameters that affect the output directly should be included.
• While making Decision Trees, one should take a look at the dataset given to them and try to figure out what
pattern does the output leaf follow. Try selecting any one output and on its basis, find out the common links
which all the similar outputs have.
Subject Enrichment
Task
1. The following is a dataset comprising 4 parameters which lead to the prediction of a student choosing
a Science stream in senior secondary school. Make decision tree for this dataset:
Aptitude Logical Skills Analytical Skills Reasoning Stream Selection: Science
High High High High Yes
High Low Low Low No
Low High High High Yes
Low Low Low High No
Low High High Low No
2. Make a decision tree to choose a book from the library based on the following selections.
Choice 1: Fiction—Sci-Fi, Mystery, Classics.
Choice 2: No Fiction—Travel Diaries, Autobiographies, History, Travelogues.
AI Project Cycle 227

