Matthew's Correlation Coefficient

URI: https://gptkb.org/entity/Matthew%27s_Correlation_Coefficient
GPTKB entity
Statements (60)
Predicate Object
gptkbp:instance_of gptkb:physicist
gptkbp:bfsLayer 5
gptkbp:bfsParent gptkb:GLUE_Benchmark
gptkbp:applies_to confusion matrices
gptkbp:distance binary outcomes
gptkbp:function four values
https://www.w3.org/2000/01/rdf-schema#label Matthew's Correlation Coefficient
gptkbp:introduced gptkb:G._P._Matthews
gptkbp:is_a_tool_for model evaluation
gptkbp:is_analyzed_in false positives
binary outcomes
false negatives
true positives
classification models
the performance of classifiers in imbalanced datasets
confusion matrix values
the accuracy of predictions
the performance of algorithms
the performance of classifiers
the reliability of predictions
true negatives
gptkbp:is_compared_to different models
the effectiveness of different algorithms
gptkbp:is_essential_for imbalanced datasets
gptkbp:is_evaluated_by evaluating predictions
evaluating risk
(TP * TN -FP * FN) / sqrt((TP + FP)(TP + FN)(TN + FP)(TN + FN))
gptkbp:is_influenced_by sample size
gptkbp:is_known_for gptkb:MCC
gptkbp:is_related_to gptkb:Cohen's_kappa
gptkbp:is_standardized_by data science
gptkbp:is_used_in gptkb:sports_team
gptkb:software_framework
research studies
clinical trials
environmental studies
financial modeling
predictive analytics
quality control
bioinformatics
data mining
medical diagnostics
social sciences
image classification
text classification
gptkbp:key gptkb:Artificial_Intelligence
statistics
model effectiveness
gptkbp:measures machine learning research
predictive accuracy
the strength of association
the correlation between observed and predicted values
the agreement between two raters
the predictive power of a model
the quality of binary classifications
gptkbp:range -1 to 1
gptkbp:sensor class imbalance
gptkbp:suitable_for accuracy in some cases
gptkbp:type_of correlation coefficient
gptkbp:used_in binary classification