C5.0

method = 'C5.0'

Type: Classification

Tuning Parameters: trials (# Boosting Iterations), model (Model Type), winnow (Winnow)

Cost-Sensitive C5.0

method = 'C5.0Cost'

Type: Classification

Tuning Parameters: trials (# Boosting Iterations), model (Model Type), winnow (Winnow), cost (Cost)

Cubist

method = 'cubist'

Type: Regression

Tuning Parameters: committees (#Committees), neighbors (#Instances)

Model Rules

method = 'M5Rules'

Type: Regression

Tuning Parameters: pruned (Pruned), smoothed (Smoothed)

Model Tree

method = 'M5'

Type: Regression

Tuning Parameters: pruned (Pruned), smoothed (Smoothed), rules (Rules)

Rule-Based Classifier

method = 'JRip'

Type: Classification

Tuning Parameters: NumOpt (# Optimizations)

Rule-Based Classifier

method = 'PART'

Type: Classification

Tuning Parameters: threshold (Confidence Threshold), pruned (Confidence Threshold)

Single C5.0 Ruleset

method = 'C5.0Rules'

Type: Classification

No Tuning Parameters

Single Rule Classification

method = 'OneR'

Type: Classification

No Tuning Parameters