Model Validation
Data Science · University of Applied Sciences · Machine Learning
This unit introduces the fundamental concepts of model validation in machine learning, including cross-validation, train-test split, and evaluation metrics. Students will learn how to assess the performance of classification and regression models and select the best model for a given task.
Zum Üben gibt es 56 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Cross-Validation Techniques (e.g.
- k-fold
- leave-one-out)
- Train-Test Split Method
- Evaluation Metrics for Classification (e.g.
- accuracy
- precision
- recall
- F1-score)
- Evaluation Metrics for Regression (e.g.
- mean squared error
- root mean squared error)
Stichworte
- Cross-Validation
- Train-Test Split
- Evaluation Metrics
- Classification
- Regression
- Model Selection
- Machine Learning
- Data Science