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Table 1 Representative algorithms in ML and DL

From: Application of machine learning in ophthalmic imaging modalities

AI TechniquesClassificationAlgorithms
Conventional Machine learningSupervised learningSVM, Linear Regression, Logistic Regression, RF, KNN, Naïve Bayesian, Decision Tree, AdaBoost, Neural network methods
Unsupervised learningPrincipal component analysis, K-means, Expectation-maximization, Mean shift, Hierarchical clustering, Affinity propagation, Iterative self-organizing data, fuzzy C-means systems
Reinforcement learningQ-learning, Temporal difference learning, State-Action-Reward-State-Action, Teaching-Box systems, Maja systems
Deep learningDBNConvolutional deep belief network, Conditional restricted Boltzmann machine
CNNAlexNet, GoogleNet, Visual geometry group network (VGG), Deep Residual Learning, Inception v4 (v2, v3), Restnet-152 (34,50,101), LeNet
RNNBidirectional RNN, Long short-term memory
  1. DBN=deep belief network; CNN = convolution neural network; RNN = recurrent neural network; SVM = support vector machine; RF = random forest; KNN = k-nearest neighbor
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