TABLE 1.

Different types of classifier features.

Classifier type	Prediction speed	Memory usage	Interpretability	Model flexibility
linSVM	Binary: Fast Multiclass: Medium	Medium	Easy	Low Makes a simple linear separation between classes
quaSVM	Binary: Fast Multiclass: Slow	Binary: Medium Multiclass: Large	Hard	Medium
cubSVM	Binary: Fast Multiclass: Slow	Binary: Medium Multiclass: Large	Hard	Medium
finGSVM	Binary: Fast Multiclass: Slow	Binary: Medium Multiclass: Large	Hard	High, creases with kernel scale setting Makes finely detailed distinctions between classes, with kernel scale set to sqrt(P)/4
medGSVM	Binary: Fast Multiclass: Slow	Binary: Medium Multiclass: Large	Hard	Medium Medium distinctions, with kernel scale set to sqrt(P)
coaGSVM	Binary: Fast Multiclass: Slow	Binary: Medium Multiclass: Large	Hard	Low Makes coarse distinctions between classes, with kernel scale set to sqrt(P)*4, where P is the number of predictors
finKNN	Medium	Medium	Hard	Finely detailed distinctions between classes. The number of neighbors is set to 1
medKNN	Medium	Medium	Hard	Medium distinctions between classes. The number of neighbors is set to 10
coaKNN	Medium	Medium	Hard	Coarse distinctions between classes. The number of neighbors is set to 100
cosKNN	Medium	Medium	Hard	Medium distinctions between classes, using a cosine distance metric. The number of neighbors is set to 10
cubKNN	Slow	Medium	Hard	Medium distinctions between classes, using a cubic distance metric. The number of neighbors is set to 10
weiKNN	Medium	Medium	Hard	Medium distinctions between classes, using a distance weight. The number of neighbors is set to 10