Dimensionality Reduction and Clustering
Bachelor of Science in Computer Science · University · Machine Learning
This unit introduces dimensionality reduction techniques, such as PCA and LDA, and clustering algorithms, such as k-means and hierarchical clustering. Students will learn how to apply these techniques to real-world data to extract meaningful insights and make informed decisions.
Zum Üben gibt es 103 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Dimensionality Reduction
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- k-means Clustering
- Hierarchical Clustering
- Applications of Dimensionality Reduction and Clustering
- Evaluation of Dimensionality Reduction and Clustering Results
Stichworte
- Dimensionality Reduction
- Clustering
- PCA
- LDA
- k-means
- Data Analysis
- Machine Learning