Machine Learning Algorithm comparison.

Comparison of various supervised machine learning algorithms. A small training set was used to compare the error rates of multiple MLAs when classifying glutamatergic and GABAergic synapses in an early data set. From left to right: Linear Discriminant Analysis (LDA); Quadratic Discriminant Analysis (QDA); Naive Bayesian filter, gaussian distribution assumption (NB); Naive Bayesian filter, normalized kernel distribution assumption (NBkd); Random Forest Ensemble (RFE); k-means clustering (kNN); Support Vector Machine (SVN). k-means clustering, an unsupervised clustering method, was included for comparison's sake.