Table 3.

Summary of arthropod machine learning model performance

	OrthoDB Arthropod EQUAL		OrthoDB Arthropod PROP
Algorithm	Validation	Testing	Validation	Testing
Neural Network	97.1815 %	96.8153 %	97.5452 %	96.5423 %
Suppor Vector Machine (SVM)	89.1351 %	88.0801 %	88.0668 %	88.2621 %
Random Forest	98.1362 %	95.9054 %	97.8748 %	95.5414 %
Naive Bayes	53.0628 %	52.5023 %	61.2229 %	60.3276 %
Logistic Regression	96.5905 %	97.2702 %	96.3064 %	96.3603 %
Meta-Classifier w/o Logistic Regression	98.5112 %	98.3621 %	98.5907 %	96.8153 %
Meta-Classifier w/ Logistic Regression	98.6362 %	97.7252 %	98.5680 %	97.5432 %

This table shows the performance of each of the different learning algorithms that were trained, validated, and tested with the OrthoDB arthropod gene clusters