Principal Component Analysis (PCA) is a dimensionality reduction technique that identifies the directions of maximum variance in data. By understanding PCA, you'll gain insights into data distribution and effectively reduce its dimensionality while preserving key information. Üben mit sofortiger Rückmeldung, kostenlos und ohne Anmeldung.

Weitere Themen

• What is Unsupervised Learning?
• Types of Unsupervised Learning
• K-Means Clustering
• Hierarchical Clustering
• Linear Discriminant Analysis (LDA)
• One-Class Support Vector Machines (OC-SVMs)
• Isolation Forests