Desicion Tree (DT) are supervised Classification algorithms.
They are:
Decision trees extract predictive information in the form of human-understandable tree-rules. Decision Tree is a algorithm useful for many classification problems that that can help explain the model’s logic using human-readable “If…. Then…” rules.
They can:
Each decision in the tree can be seen as an feature.
The creation of a tree is a quest for:
At each level, choose the attribute that produces the “purest” nodes (ie choosing the attribute with the highest information gain)
Algorithm:
Decision Trees are prone to overfitting:
Decision Trees can overfit badly because of the highly complex decision boundaries it can produce; the effect is ameliorated, but rarely completely eliminated with Pruning.
if Ticket Class = "1" then
if Sex = "female" then Survive = "yes"
if Sex = "male" and age < 5 then Survive = "yes"
if Ticket Class = "1" then
if Sex = "female" then Survive = "yes"
if Sex = "male" then Survive = "no"
if Ticket Class = "3"
if Sex = "male" then Survive = "no"
if Sex = "female" then
if Age < 4 then Survive = "yes"
if Age >= 4 then Survive = "no"
Every path from the root is a rule
Single tests at the nodes
Compound tests at the nodes