Issue 58

A. Mishra et alii, Frattura ed Integrità Strutturale, 58 (2021) 242-253; DOI: 10.3221/IGF-ESIS.58.18

A DA BOOST ALGORITHM

A

daBoost is also known as Adaptive boosting falls into the classification category of ensemble boosting as shown in Fig. 14. The multiple weak classifiers are combined to increase the accuracy of the classifiers. Adaptive boosting works on an iterative ensemble method that allocates the weights of the classifiers and further data samples are trained in each iteration step.

Figure 14: Working Mechanism of Adaptive Boosting algorithm. Tab. 5 shows the classification report of Ada Boost algorithm and Fig. 15 shows its performance. It is observed that the Ada Boost algorithm resulted in lowest accuracy score of 0.56 in comparison to the other algorithms. Precision Recall F1-score 0 0.00 0.00 0.00 1 0.83 0.62 0.71 Accuracy 0.56 Macro average 0.42 0.31 0.36 Weighted average 0.74 0.56 0.63 Table 5: Classification report of Ada Boost algorithm.

Figure 15: Confusion Matrix showing the performance of Ada Boost Algorithm.

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