A decision tree is a flowchart-like structure in which each internal node represents a test on a feature (e.g. whether a coin flip comes up heads or tails) , each leaf node represents a class label (decision taken after computing all features) and branches represent conjunctions of features that lead to those class.
A decision tree has the substantial advantage of forcing the evaluation of all conceivable outcomes of a decision and tracing each path to a conclusion. It generates a complete analysis of the effects along each branch and flags decision nodes that require additional investigation.
A decision tree makes its decision by running a series of tests.
The ID3 (by Quinlan) algorithm is the fundamental method utilized in decision trees. The ID3 algorithm constructs decision trees in a top-down, greedy manner.
Learner's Ratings
4.6
Overall Rating
62%
38%
0%
0%
0%
Reviews
R
Rohit Khare
4
What will be the mandatory requirement of configuration of PC for this ML tool
M
Muhammad Fahad Bashir
5
Explained the concept easily
P
Pradeep Kumar Kaushik
5
Please give me iris,csv file.
A
Ankit Malik
4
where is the finaldata.csv
V
Vimal Bhatt
5
great learning plateform kushal sir is really too good
Share a personalized message with your friends.