Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Artificial_Intelligence
|
| gptkbp:analyzes |
tree structure
flowchart |
| gptkbp:applies_to |
finance
large datasets text classification |
| gptkbp:based_on |
gptkb:C4.5_algorithm
|
| gptkbp:can_be_used_with |
ensemble methods
|
| gptkbp:can_create |
if-then rules
multiple trees |
| gptkbp:controls |
imbalanced datasets
continuous and categorical data |
| gptkbp:developed_by |
gptkb:Ross_Quinlan
|
| gptkbp:exported_to |
gptkb:Specification
|
| https://www.w3.org/2000/01/rdf-schema#label |
J48
|
| gptkbp:is_a |
classifier
|
| gptkbp:is_compatible_with |
big data technologies
cross-validation |
| gptkbp:is_effective_against |
binary classification
|
| gptkbp:is_evaluated_by |
gptkb:municipality
F1 score ROC curve accuracy confusion matrix precision |
| gptkbp:is_implemented_in |
gptkb:R_programming_language
gptkb:Java gptkb:Weka gptkb:Library |
| gptkbp:is_known_for |
simplicity
robustness interpretability handling missing values |
| gptkbp:is_part_of |
data analysis
machine learning algorithms predictive analytics supervised learning Weka software suite |
| gptkbp:is_popular_in |
machine learning community
|
| gptkbp:is_used_for |
risk assessment
predictive modeling spam detection |
| gptkbp:is_used_in |
healthcare
e-commerce bioinformatics social media analysis marketing analytics |
| gptkbp:is_used_to |
identify patterns
predict outcomes |
| gptkbp:is_utilized_in |
customer segmentation
|
| gptkbp:produced_by |
decision trees
|
| gptkbp:provides |
rules for classification
|
| gptkbp:suitable_for |
classification tasks
real-time analysis |
| gptkbp:supports |
pruning
|
| gptkbp:tuning |
hyperparameter optimization
|
| gptkbp:used_in |
data mining
|
| gptkbp:bfsParent |
gptkb:Grumman_F9_F_Panther
|
| gptkbp:bfsLayer |
4
|