Category:Statistical classification

• Statistical classification

A

• Averaged one-dependence estimators
• Automated essay scoring

B

• Bayes classifier
• Bayes error rate
• Bias–variance tradeoff
• Binary classification

C

• Calibration (statistics)
• Chi-square automatic interaction detection
• Classification rule
• Confusion matrix
• Cover's theorem

D

• Data classification (business intelligence)
• Decision boundary
• Double descent

E

• Evaluation of binary classifiers

F

• False positives and false negatives
• Firmographics

G

• Geodemographic segmentation
• Growth function

H

• Ho–Kashyap rule

I

• Industrial market segmentation

K

• K-nearest neighbors algorithm
• Kernel Fisher discriminant analysis
• Kernel perceptron
• Klecka's tau

L

• Leakage (machine learning)
• Least-squares support vector machine
• Linear classifier
• Linear discriminant analysis

M

• Margin classifier
• Mixture (probability)
• Multiclass classification
• Multiclass LDA
• Multinomial probit
• Multiple discriminant analysis

N

• Naive Bayes classifier
• Natarajan dimension
• Neighbourhood components analysis
• Net reclassification improvement

O

• One-class classification

P

• Partial Area Under the ROC Curve
• Phi coefficient
• Platt scaling
• Predictive modelling
• Prior knowledge for pattern recognition
• Proaftn
• Probabilistic classification
• Probability matching
• Pronunciation assessment

Q

• Quadratic classifier

R

• Receiver operating characteristic
• Recursive partitioning
• Root Cause Analysis Solver Engine

S

• Sagacity segmentation
• Sensitivity and specificity
• Similarity measure
• Support vector machine

T

• Total operating characteristic
• Typology (social science research method)

V

• Values Modes
• Vapnik–Chervonenkis dimension
• Variable kernel density estimation

Y

• Youden's J statistic