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Some of the methods are shown to be capable of achieving a prediction accuracy which can be utilised by industry for planning and automating new designs of steel.
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Our best performance achieves a prediction accuracy of 67.9%.
The n-MMC algorithm managed to achieve a prediction accuracy ranging from 70 to 95%%.
It is especially interesting that five of the six algorithms achieved a prediction accuracy of more than 90%.
As an application, we use the model for population predication in three data sets, and it can achieve a prediction accuracy between 86.14% and 99.89%.
By comparing the predicted population with ground-truth values, the results show that our model can achieve a prediction accuracy between 86.14% and 99.89%.
Moreover, they used 190 mixed Markov-chain models to achieve the prediction accuracy of 64%%, whilst one Markov-chain model with one transition matrix for the 691 participants was able to achieve a prediction accuracy of 45.6 %.
The proposed method can achieve a prediction accuracy of 98.28% and 97.87% on a stringent Gram-positive (Gpos) and Gram-negative (Gneg) dataset with Jackknife test, respectively.
As an application, we further utilize the model to predict population growth in three data sets, which illustrates that our model can achieve a prediction accuracy between 86.14% and 99.89%.
This new index takes into account the effective rainfall, in addition to topographic factors, in order to achieve a prediction of wetland occurrence for places with different rainy conditions.
These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com