twenty two.Among machine learning algorithms, which of the following is not unsupervised learning?

The correct answer is B. Xgboost. XGBoost (B) is a supervised learning algorithm - it trains an ensemble of gradient-boosted decision trees to predict a labeled target variable, meaning it requires input-output pairs during training. GMM (Gaussian Mixture Models) is unsupervised, fitting a probabilistic model…

Machine Learning Basics

Question

Options

AGMM
BXgboost
CClustering
DAssociation rules

How the community answered

(42 responses)

A
2% (1)
B
79% (33)
C
14% (6)
D
5% (2)

Explanation

XGBoost (B) is a supervised learning algorithm - it trains an ensemble of gradient-boosted decision trees to predict a labeled target variable, meaning it requires input-output pairs during training. GMM (Gaussian Mixture Models) is unsupervised, fitting a probabilistic model to discover latent cluster structure in unlabeled data. Clustering algorithms (e.g., K-means, DBSCAN) are the textbook unsupervised category, grouping data by similarity with no ground-truth labels. Association Rules (e.g., Apriori) mine co-occurrence patterns from unlabeled transaction data - also unsupervised.

Memory tip: Supervised = needs a "supervisor" (labels/answers). XGBoost is a boosting method - it's always boosting toward a target, so it must be supervised. If an algorithm can run on raw, unlabeled data, it's unsupervised.

Topics

#Supervised Learning#Unsupervised Learning#XGBoost#Algorithm Classification

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