Unsupervised Learning Quiz: Test Your Knowledge

📚 Unsupervised Learning Quiz: Test Your Knowledge

🧠 Quick Study Guide

• 📊 Definition: Unsupervised learning algorithms learn from unlabeled data to find patterns and structures.
• 🧩 Clustering: Groups similar data points together. Common algorithms include K-means, Hierarchical clustering, and DBSCAN.
• 📉 Dimensionality Reduction: Reduces the number of variables while preserving important information. PCA (Principal Component Analysis) is a key technique.
• 🔍 Association Rule Learning: Discovers relationships between variables in large datasets. Apriori algorithm is often used.
• 💡 K-Means Clustering: Aims to partition $n$ observations into $k$ clusters, where each observation belongs to the cluster with the nearest mean (cluster center or centroid).
• 🐍 PCA Formula: The principal components are eigenvectors of the covariance matrix of the original data. $Cov(X)v = \lambda v$, where $X$ is the data, $v$ is an eigenvector, and $\lambda$ is an eigenvalue.
• ⏱️ Use Cases: Customer segmentation, anomaly detection, recommendation systems, and image compression.

🧪 Practice Quiz

1. Question 1: Which of the following is NOT a type of unsupervised learning?
   1. Clustering
   2. Regression
   3. Dimensionality Reduction
   4. Association Rule Learning
2. Question 2: Which algorithm is commonly used for dimensionality reduction?
   1. Linear Regression
   2. K-Nearest Neighbors
   3. Principal Component Analysis (PCA)
   4. Support Vector Machine (SVM)
3. Question 3: What is the primary goal of clustering?
   1. Predicting future values
   2. Grouping similar data points together
   3. Finding the best decision boundary
   4. Reducing the number of features
4. Question 4: Which of the following algorithms is a density-based clustering algorithm?
   1. K-means
   2. Hierarchical Clustering
   3. DBSCAN
   4. PCA
5. Question 5: In K-means clustering, what does 'K' represent?
   1. The number of data points
   2. The number of clusters
   3. The number of iterations
   4. The number of features
6. Question 6: Which of the following is an application of association rule learning?
   1. Predicting stock prices
   2. Customer segmentation
   3. Image classification
   4. Recommendation systems
7. Question 7: What type of data is typically used in unsupervised learning?
   1. Labeled data
   2. Unlabeled data
   3. Time-series data
   4. Categorical data