Titlebook: Bangabandhu and Digital Bangladesh; First International A. K. M. Muzahidul Islam,Jia Uddin,Shah Murtaza Ra Conference proceedings 2022 The

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https://doi.org/10.1007/978-3-662-25601-510-fold cross validation procedure in this study. We have also employed the Bagging ensemble approach with Random Forest to improve the result. Our suggested model has given 85.18% accuracy through Recursive Feature Elimination with Bagging (Random Forest).

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,Eigenschaften der Flüssigkeiten,sifier, Random Forest, Support Vector Machine) to predict whether a person has cardiovascular disease or not. We applied a raw dataset with 12 attributes and our engineered dataset with 16 attributes on these algorithms. In both dataset number of data points were 62500. After analyzing the accuracy,

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Schnittgeschwindigkeiten und Vorschübet201, and InceptionResNetV2 were utilized to tag COVID-19 as negative or positive in case of the CT scan inputs. Our used transfer learning based Xception, MobileNetV2, InceptionV3, DenseNet201, and IncpetionResNetV2 achieved the highest validation accuracy of 92.19%, 97.40%, 85.42%, 86.98%, and 95.

金哥占卜者

Salesforce-Integrationsarchitektur,ord Error Rate (WER) of 42.15%. We tested our developed database management architecture for the Interaction Recognition system with the three-step evaluation using BERT sentence transformer (paraphrase-mpnet-base-v2) that provided satisfactory responses with 92% accuracy, increasing the receptionis