Classification algorithm hyperparameter combinations. by Stephen R. Piccolo (8367780)

Feature-selection algorithm hyperparameter combinations. by Stephen R. Piccolo (8367780)

Comparison of ranks for classification algorithms across performance metrics. by Stephen R. Piccolo (8367780)

Tradeoff between execution time and predictive performance for classification algorithms. by Stephen R. Piccolo (8367780)

Relative classification performance per combination of feature-selection and classification algorithm. by Stephen R. Piccolo (8367780)

Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

“…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”

Relative performance of classification algorithms using gene-expression and clinical predictors and performing feature selection. by Stephen R. Piccolo (8367780)

Prediction results of individual models. by Ahmed M. Elshewey (21463867)

“…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression predictors. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using clinical predictors. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection. by Stephen R. Piccolo (8367780)

The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

“…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”

Chinese-STS-B dataset. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”

Ablation test results for character matching. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”

Image space visualization results. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”

Evaluation result of competition datasets. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”

Dot matrix space visualization results. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”

Reconstruction result. by Meilong Zhu (17200360)

“…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …”