Decision Tree Algorithm

Decision Tree क्या है?

Decision Tree ka matlab hai: A Decision Tree makes predictions using a tree-like structure of questions and decisions. Simple words me, ye topic practical Python programs likhne me direct use hota hai.

Is topic ko sirf definition ke liye nahi, balki rule-based decisions jaise real examples ke liye practice karein.

यह क्यों सीखना जरूरी है?

• Ye rule-based decisions me kaam aata hai.
• Ye explainable classification se bhi connected hai.
• Isse aap code ka output aur errors better samajh paate hain.

Important Terms

Syntax / Basic Pattern

Basic idea: pehle data तैयार करें, phir Python logic apply करें, aur finally result display करें.

from sklearn.tree import DecisionTreeClassifier
X = [[30], [45], [60], [75], [90]]
y = ["Fail", "Fail", "Pass", "Pass", "Pass"]
model = DecisionTreeClassifier(random_state=0)
model.fit(X, y)
print(model.predict([[55]])[0])

Complete Example Program

from sklearn.tree import DecisionTreeClassifier

X = [[30], [45], [60], [75], [90]]
y = ["Fail", "Fail", "Pass", "Pass", "Pass"]

model = DecisionTreeClassifier(random_state=0)
model.fit(X, y)
print(model.predict([[55]])[0])

Expected Output

Program Explanation

• from sklearn.tree import DecisionTreeClassifier imports ready-made features from a module/library.
• X = [[30], [45], [60], [75], [90]] stores a value in X.
• y = ["Fail", "Fail", "Pass", "Pass", "Pass"] stores a value in y.
• model = DecisionTreeClassifier(random_state=0) stores a value in model.
• model.fit(X, y) performs the next step of the program logic.
• print(model.predict([[55]])[0]) displays information or calculated result on the screen.

Practical Uses

• Rule-based decisions.
• Explainable classification.
• Visual model explanation.

Common Mistakes

• Training and testing the model on the same data.
• Using an algorithm without understanding the input features.
• Reporting only accuracy without checking actual mistakes and limitations.

Practice Tasks

1. Program ko decision-tree.py file me type karke run karein.
2. Values change karke output compare karein.
3. rule-based decisions par ek छोटा example banayen.
4. Logic ko apne words me 5 lines me likhein.

सारांश

Decision Tree ko tab complete maanenge jab aap iska meaning, example, output aur practical use clearly explain kar saken.