Friedman test for classification error rate, ranked first results are shown in bold. by Genliang Li (5816264)

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Data of pregnant woman. by Natsumi Nishiyama (19928990)

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Table 2_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.docx by Xinrui Wang (488330)

“…After min-max normalization, six classification models—KNN, AdaBoost, Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and XGBoost—were developed, and the Sparrow Search Algorithm (SSA) was employed to optimize hyperparameters for enhanced performance.…”

Table 1_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.xlsx by Xinrui Wang (488330)

“…After min-max normalization, six classification models—KNN, AdaBoost, Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and XGBoost—were developed, and the Sparrow Search Algorithm (SSA) was employed to optimize hyperparameters for enhanced performance.…”

Data categories of the experimental corpus. by Ming Gao (115719)

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Data Categories of the Sogou Corpus. by Ming Gao (115719)

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Data types and their sources. by Firdissa Sadeta Tiye (21222102)

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The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC12. by Aninda Astuti (21736334)

The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC11. by Aninda Astuti (21736334)

The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC10. by Aninda Astuti (21736334)

Custom UNET and UNET-GRU performance metrics for burnt area classification using Bandipur PlanetScope data. by Sai Balakavi (21728626)

Left. Calibration curves for 3-label classification in Model 1 (statistical features only). Right. Calibration curves for 3-label classification in Model 2 (Model 1 features + temp... by Jamison H. Burks (21029607)

Data for defining optimum threshold. by Natsumi Nishiyama (19928990)

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Comparison of performance metrics, SVC vs QSVC after using NQE for data embedding. Bold-faced fonts denote that the classifier achieves better performance. by Aninda Astuti (21736334)

The Wilcoxon rank sum test for classification error rates, where no difference is shown in bold. by Genliang Li (5816264)

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Consistency results of raw data. by Haotong Han (20855036)

Data Categories of the CNTC News Corpus. by Ming Gao (115719)

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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this an... by Aninda Astuti (21736334)

Classification report for the nids-fgpa model. by JiaMing Wang (334865)