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Table 3 On-board runtime and storage requirement of four machine learning methods with full feature sets and simplified feature set

From: An evaluation of machine learning classifiers for next-generation, continuous-ethogram smart trackers

  SVM RF ANN XGBoost
Runtime(ms)
 Full feature set 43.042 2.154 1.044 0.312
 Simplified feature set 34.628 0.186 0.826 0.134
Storage requirement(kB)
 Full feature set 185.684 164.808 10.764 24.3
 Simplified feature set 26.724 23.064 3.42 13.164
  1. SVM Support vector machine, RF Random forest, ANN Artificial neural network, XGBoost Extreme gradient boosting
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