The correlation results graph between the number of classifications (K) and the GVF for each combination. by Xiaojie Feng (6873953)

Subjects: “…hierarchical clustering algorithm…”

Comparative overview of all DL and ML algorithms parameters in used in this study. by Khandaker Mohammad Mohi Uddin (13124356)

A comparison of the proposed method with image classification models on the ImageNet-Hard dataset. by Ebrahim Parcham (20700216)

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State-of-the-Art Skin Disease Classification Using Ensemble Learning and Advanced Image Processing by Nirupama (22148684)

“…Then the feature extraction is performed using the Gray Level Co-occurrence Matrix. For classification, the Meta Ensemble-based Random Cat Gradient Boost model is introduced by combining the merits of multiple classifiers to enhance prediction performance. …”

Comparison of burnt area classification using UNET and UNET-GRU models. by Sai Balakavi (21728626)

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Evaluation of burnt area classification performance near a water body. by Sai Balakavi (21728626)

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Evaluating Burnt area classification on fragmented burnt regions with smaller patches. by Sai Balakavi (21728626)

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A comparison of the CRN-SMOTE and RN-SMOTE methods on the health risk dataset based on different classification metrics using the Random Forest classifier. by Javad Hemmatian (20700209)

Data mining classification. by Yongkang Ding (21807539)

Data from an Investigation of Music Analysis by the Application of Grammar-based Compressor by David Humphreys (19079318)

“…<br>Number of patterns identified the by algorithm.<br>Establishment precision.<br>Establishment recall.…”

Performance metrics of the proposed DRSA-based model on the Unseen data. by Saim Chishti (22272188)

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Classification performances of Ensemble, SVM, and kNN algorithms. For each performance metric, the mean value across all runs and standard deviation of the mean value is reported i... by Ayşenur Eser (21713911)

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.…”

Time-based splitting strategy and forecast horizons. by Thierry Jean (20691795)

Results of oil status recognition accuracy in the test set across iteration cycles under different algorithms. by Shiya Gao (12693389)

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Results of Oil Condition Recognition Accuracy in the Training Set Under Different Algorithms Across Iteration Cycles. by Shiya Gao (12693389)

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Comparing AUROC across several deep learning techniques for the classification of sepsis on complete blood count data (higher values represent better performance). We evaluated the... by Daniel Walke (21680915)

Flow chart of Novel enhanced DBSCAN based model. by Shahneela Pitafi (20454775)

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Ensemble learning model prediction results based on text indicators. by Zhiheng Zhang (9347282)

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