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Fig 1.

Methodological steps.

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Fig 2.

Markowitz frontier, minimum generalization error asset, and portfolio.

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Fig 3.

Dimensional variables of I-beam [87].

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Fig 4.

Five types of Beta functions considered.

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Fig 5.

Radial dendrogram obtained from DBHT algorithm with Pearson correlation distance and generalization error similarity.

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Fig 6.

Radial dendrogram obtained from DBHT algorithm with Kendall’ τ correlation distance and generalization error similarity.

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Fig 7.

Radial dendrogram obtained from DBHT algorithm with Spearman’s ρ correlation distance and generalization error similarity.

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Fig 8.

Model selection for each clustering algorithm considered.

For color blindness accessibility, the legend’s first(second) row describes the first(second) column of the grid.

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Fig 9.

Results for all bounded weights stacking strategies.

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Fig 10.

Heatmap of weights.

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Fig 11.

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,5), i.e., the center of mass of the distribution closer to the left end of the interval, according to their respective physical ranges.

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Fig 12.

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,2), i.e., the center of mass of the distribution at the center of the interval, according to their respective physical ranges.

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Fig 13.

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(5,2), i.e., the center of mass of the distribution closer to the right end of the interval, according to their respective physical ranges.

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Fig 14.

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(0.5,0.5), i.e., two centers of mass for the distribution located at both the right and left ends of the interval, according to their respective physical ranges.

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Fig 15.

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(1,1), i.e., uniform distribution over the interval, according to their respective physical ranges.

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Fig 16.

Comparison of mean performance metric for probabilities of failure calculations considering all the input variables.

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