Classification accuracy with others CNNs algorithms. by Jun Tan (46388)

Flowchart of the framework of text classification algorithm for subordinate classes of tourist attractions. by Lu Xiao (314030)

Subjects:

Parent class classification label. by Rong Zhou (138287)

Algorithm assessment of temporal drought class using TPM. by Muhammad Asif Khan (7367468)

Class distribution for 5-class classification. by Toheeb Salahudeen (21368040)

“…RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. …”

Class distribution for 3-class classification. by Toheeb Salahudeen (21368040)

“…RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. …”

RF classification algorithm comparison before and after dataset expansion. by Chao Tang (10925)

Comparison of resnet classification algorithm before and after dataset expansion. by Chao Tang (10925)

Features selection using the Boruta algorithm. by Nishat Tasnim Thity (21755858)

Subjects:

Confusion matrix for RUSBoost algorithm (3000 Learning Cycles) highlights the classification accuracy across different classes. by Sadia Nazim (21440115)

“…<p>Confusion matrix for RUSBoost algorithm (3000 Learning Cycles) highlights the classification accuracy across different classes.…”

Confusion matrix for Random Forest algorithm (3000 Number of trees) highlights the classification accuracy across different classes. by Sadia Nazim (21440115)

“…<p>Confusion matrix for Random Forest algorithm (3000 Number of trees) highlights the classification accuracy across different classes.…”

Average classification accuracies for fft and stack methods, LSTM, Bi-LSTM, and CNN algorithms. by Jamila Akhter (21144252)

Class distribution of dataset. by Vaibhav Gadag (20642471)

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Fuzzy rule algorithm for severity assessment. by Chatla Subbarayudu (21368330)

Comparison of ResNet Classification Algorithm Expansion Experiments with Similar Data Enhancement Models. by Chao Tang (10925)

Comparison of in the negative class. by André G. Coimbra (21354135)

Definition of LULC classes. by Firdissa Sadeta Tiye (21222102)

RF Algorithm Principles. by Zhiheng Zhang (9347282)

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5.FCV procedure used for classification. by Ebru Ergün (21395498)

Subjects:

ML algorithms used in this study. by Toheeb Salahudeen (21368040)

“…RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. …”