Fundamentals and Methods of Machine and Deep Learning. Pradeep Singh

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Fundamentals and Methods of Machine and Deep Learning - Pradeep Singh


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data is required for training, and so on.

      Figure 2.6 A high-level representation of stacking.

Technique Accuracy Throughput Execution time Response time Error rate Learning rate
Bayes optimal classifier Low Low High Medium Medium Low
Bagging Low Medium Medium High Low Low
Boosting Low Medium High High High Low
Bayesian model averaging High High Medium Medium Low Low
Bayesian model combination High High Low Low Low High
Bucket of models Low Low High Medium Medium Low
Stacking High High Low Low low Medium

      This chapter provides introduction to zonotic diseases, symptoms, challenges, and causes. Ensemble machine learning uses multiple machine learning algorithms to identify the zonotic diseases in early stage itself. Detailed analysis of some of the potential ensemble machine learning algorithms, i.e., Bayes optimal classifier, bootstrap aggregating (bagging), boosting, BMA, Bayesian model combination, bucket of models, and stacking are discussed with respective architecture, advantages, and application areas. From the analysis, it is observed that the efficiency achieved by Bayesian model combination, stacking, and Bayesian model combination are high compared to other ensemble models considered for identification of zonotic diseases.

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