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Advances, Systems and Applications

Journal of Cloud Computing Cover Image

Table 4 The machine learning models and utilised parameters

From: Online architecture for predicting live video transcoding resources

Model Parameters
RL Neural network = Input: 25 Integers; 3*(32 Unit layers+RELUs), output: Integer (linear activation)
DQN Agent (target_model_update = 1e-3, nb_steps_warmup = 50, policy = Boltzmann Q Policy), Adam Optimizer (learning rate = 1e-2), Training steps = 4000
Reward: 0.4 (goal achieved), −0.5 (goal not achieved)
RF RandomForestRegressor(n_estimators = 100)
SGD SGDRegressor (max_iter = 1000)