Accuracy of the Random forest algorithm for different values of test samples and different choice of random states. by Abeer Aljohani (18497914)

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Accuracy of the Random forest algorithm for different values of test samples and different choice window indexes. by Abeer Aljohani (18497914)

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Improved random forest algorithm. by Zhen Zhao (159931)

“…The random forest was constructed using feature subsets that were selected via different feature selection methods, namely MIC-RF, RFECV-RF and MDA-RF. …”

Parametric study of accuracy of the Random forest algorithm for different proportions of test samples and different choice of random states. by Abeer Aljohani (18497914)

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General model performance for different algorithms. by Binghan Xue (21253235)

Performance of models by different algorithms. by Yong Zhang (5893)

Pseudocode for the missForestPredict algorithm. by Elena Albu (15181070)

“…This allows users to tailor the imputation to their specific needs. The missForestPredict algorithm is compared to mean/mode imputation, linear regression imputation, mice, k-nearest neighbours, bagging, miceRanger and IterativeImputer on eight simulated datasets with simulated missingness (48 scenarios) and eight large public datasets using different prediction models. missForestPredict provides competitive results in prediction settings within short computation times.…”

Performance comparison of different adoption algorithms in XGBoost model. by Wenguang Li (6528113)

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.…”

Model performance in ROC space across different algorithms and task conditions. by Yuqi Cheng (428511)

Crop yield prediction accuracy using different ML algorithms. by Gourab Saha (8987405)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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Prediction percentage distribution using different algorithms applied in our research. by Md Junayed Hossain (22615268)

Convergence behavior of different optimization algorithms as feature selectors for SR prediction for (a) dataset-1 and (b) dataset-2. by Ibrahim Al-Shourbaji (20460541)

Confusion matrix values for different size of test samples and different choice of random states. by Abeer Aljohani (18497914)

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(a) The schematic diagram of negative sample sampling; (b) The framework of the random forest classification algorithm. by Feng Chen (25347)

Prediction results of different models. by Qinghua Li (398885)

Subjects: “…heuristic optimisation algorithms…”

Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training. by Abeer Aljohani (18497914)

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Corporate operational risk indicator statistical differences results. by Xini Fang (20861990)

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