Statements (61)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Model
|
| gptkbp:allows |
Linearity assumption
|
| gptkbp:analyzes |
ROC curve
|
| gptkbp:applies_to |
Political science
Time-to-event data |
| gptkbp:based_on |
Logistic function
|
| gptkbp:can_be_extended_by |
Multinomial logistic regression
|
| gptkbp:can_be_used_with |
Ensemble methods
|
| gptkbp:can_provide |
Interpretability of coefficients
|
| gptkbp:controls |
Categorical predictors
|
| gptkbp:developed_by |
gptkb:David_Cox
|
| gptkbp:first_introduced |
gptkb:1958
|
| gptkbp:has_achievements |
Customer churn
|
| gptkbp:has_impact_on |
Independence of observations
|
| https://www.w3.org/2000/01/rdf-schema#label |
Logistic Regression
|
| gptkbp:input_output |
Probability values
|
| gptkbp:is_analyzed_in |
Customer behavior
Survey data |
| gptkbp:is_atype_of |
Generalized linear model
|
| gptkbp:is_effective_against |
Multicollinearity
|
| gptkbp:is_enhanced_by |
Feature engineering
Lasso or Ridge regression |
| gptkbp:is_evaluated_by |
F1 score
Precision and recall Confusion matrix AIC or BIC Area under the curve (AUC) Log-likelihood |
| gptkbp:is_implemented_in |
gptkb:R_programming_language
Various statistical software Python libraries like scikit-learn |
| gptkbp:is_often_compared_to |
gptkb:Support_vector_machines
Decision trees |
| gptkbp:is_often_used_in |
Finance
Human resources Machine learning Medical research Public health research Marketing analytics Retail analytics |
| gptkbp:is_popular_in |
Social sciences
|
| gptkbp:is_related_to |
Odds ratio
|
| gptkbp:is_used_by |
Probabilities of outcomes
|
| gptkbp:is_used_for |
Binary classification
Spam detection Risk prediction |
| gptkbp:is_used_in |
Epidemiology
Credit scoring Quality control |
| gptkbp:related_model |
Binary outcomes
Probability of default |
| gptkbp:requires |
Independent variables
Large sample sizes for accuracy |
| gptkbp:sensor |
gptkb:Outliers
|
| gptkbp:suitable_for |
High-dimensional data without regularization
Highly imbalanced datasets Non-linear relationships |
| gptkbp:bfsParent |
gptkb:Decision_Trees
gptkb:AT&_T_Bell_Laboratories gptkb:Scikit-learn |
| gptkbp:bfsLayer |
4
|