Properties (58)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
software
|
| gptkbp:appliesTo |
binary classification
|
| gptkbp:developedBy |
gptkb:Robert_Schapire
gptkb:Yoav_Freund |
| gptkbp:hasContent |
computationally intensive
reduces bias improves model performance overfitting risk |
| https://www.w3.org/2000/01/rdf-schema#label |
AdaBoost
|
| gptkbp:improves |
classification accuracy
|
| gptkbp:isInfluencedBy |
class imbalance
model complexity feature selection training data quality |
| gptkbp:isLocatedIn |
MATLAB
R scikit-learn |
| gptkbp:isPartOf |
artificial intelligence
data mining predictive modeling supervised learning statistical learning theory |
| gptkbp:isRelatedTo |
machine learning
decision trees support vector machines boosting classification algorithms k-nearest neighbors gradient boosting random forests |
| gptkbp:isStudiedIn |
outliers
noisy data |
| gptkbp:isUsedFor |
F1 score
confusion matrix cross-validation multi-class classification hyperparameter optimization accuracy score base estimator selection learning rate adjustment number of estimators other ensemble methods ROC_curve |
| gptkbp:isUsedIn |
financial forecasting
image recognition risk assessment recommendation systems spam detection text classification marketing analytics face detection customer churn prediction healthcare_analytics |
| gptkbp:requires |
base learners
|
| gptkbp:type |
ensemble learning
|
| gptkbp:uses |
adaptive boosting
|
| gptkbp:worksOn |
combining weak classifiers
|
| gptkbp:yearEstablished |
1995
|