Fitting a Logistic Regression Model
Machine Learning · Further Education · Supervised Learning
This unit introduces the concept of fitting a logistic regression model to data. Students will learn how to find the values of the model parameters that maximize the likelihood of the data.
Zum Üben gibt es 54 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to logistic regression
- The logistic function
- The likelihood function
- Maximum likelihood estimation
- Model selection
- Interpretation of results
- Assumptions of logistic regression
- Advantages and disadvantages of logistic regression
- Overfitting and underfitting
- Applications of logistic regression
Stichworte
- Logistic Regression
- Model Fitting
- Likelihood Function
- Maximum Likelihood Estimation
- Model Parameters
- Data Analysis
- Classification
- Probability
- Odds
- Logit