Logistic Regression
Bachelor of Science in Computer Science · University · Machine Learning
This unit introduces logistic regression, a fundamental technique for binary classification tasks. Students will explore model formulation, parameter estimation, and applications of logistic regression in real-world scenarios.
Zum Üben gibt es 50 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Logistic Regression
- Logistic Function and Sigmoid Curve
- Model Formulation and Parameter Estimation
- Maximum Likelihood Estimation
- Model Evaluation and Interpretation
- Odds Ratio and Probability Estimation
- Decision Boundary and Classification
- Confusion Matrix and ROC Curve
- AUC and Model Selection
- Assumptions and Limitations of Logistic Regression
Stichworte
- Logistic Function
- Binary Classification
- Model Fitting
- Odds Ratio
- Probability Estimation
- Decision Boundary
- Confusion Matrix
- ROC Curve
- AUC