Train-Test Split और Data Preparation

Train Test Split क्या है?

Train Test Split ka matlab hai: Train-test split divides data into training data for learning and testing data for checking performance. Simple words me, ye topic practical Python programs likhne me direct use hota hai.

Is topic ko sirf definition ke liye nahi, balki testing on unseen data jaise real examples ke liye practice karein.

यह क्यों सीखना जरूरी है?

• Ye testing on unseen data me kaam aata hai.
• Ye checking fair performance 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.model_selection import train_test_split
X = [[1], [2], [3], [4], [5]]
y = [40, 50, 60, 70, 80]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)
print("Train size:", len(X_train))
print("Test size:", len(X_test))

Complete Example Program

from sklearn.model_selection import train_test_split

X = [[1], [2], [3], [4], [5]]
y = [40, 50, 60, 70, 80]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)
print("Train size:", len(X_train))
print("Test size:", len(X_test))

Expected Output

Program Explanation

• from sklearn.model_selection import train_test_split imports ready-made features from a module/library.
• X = [[1], [2], [3], [4], [5]] stores a value in X.
• y = [40, 50, 60, 70, 80] stores a value in y.
• X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_ stores a value in X_train, X_test, y_train, y_test.
• print("Train size:", len(X_train)) displays information or calculated result on the screen.
• print("Test size:", len(X_test)) displays information or calculated result on the screen.

Practical Uses

• Testing on unseen data.
• Checking fair performance.
• Avoiding overfitting.

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 train-test-split.py file me type karke run karein.
2. Values change karke output compare karein.
3. testing on unseen data par ek छोटा example banayen.
4. Logic ko apne words me 5 lines me likhein.

सारांश

Train Test Split ko tab complete maanenge jab aap iska meaning, example, output aur practical use clearly explain kar saken.