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CampusEduX

Problem 1: Train a Bagging Classifier

Easypython
Learn the Concept: Ensemble Techniques

Problem Description

Write a Python program that trains a BaggingClassifier using Decision Trees as the base estimator, and predicts the class for a new data point.

Input

A labeled dataset and one new data point.

Output

The predicted class.

Constraints

  • At least 8 labeled examples.

Example Input

text
X=[[1,60],[2,65],[8,95],[9,98],[4,72],[6,88],[3,68],[7,91]], y=[0,0,1,1,0,1,0,1], new=[[5,80]]

Example Output

text
Prediction: [1]

Concepts Covered

BaggingClassifier, .fit(), .predict().

Related Problems

  • Problem 2: Train an AdaBoost Classifier
    Easy · python
    Solve Problem
  • Problem 3: Compare Gradient Boosting with Different n_estimators
    Easy · python
    Solve Problem
  • Problem 4: Build a Stacking Classifier with Two Base Models
    Easy · python
    Solve Problem

Input (stdin)

Output

Run your code to see output here...