GenSearch algorithm. حسب Tarun Khajuria (12117309)

الموضوعات:

Algorithm detection steps. حسب José M. Rivera-Arbeláez (12418512)

Algorithm pseudocode. حسب Cheng-jie Chen (22272090)

الموضوعات:

Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

"…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …"

Example measurement and analysis units for landscape elements. حسب Jaewon Han (8660295)

الموضوعات:

Risk Groups Immune Infiltration Analysis by ssGSEA Algorithm. حسب Yongling Wang (13261656)

Identification of CRG based on WGCNA algorithm. حسب Lin Feng (84785)

Accuracy and average dots covered for difficulty level 11 using gradient descent to find the optimal solution. حسب Tarun Khajuria (12117309)

الموضوعات:

The method for determining the chemical constituents of unknown materials in the algorithm. حسب Dong Hyeok Choi (12562048)

Averaged absorption spectra as a function of cost <i>χ</i> for varying light environments (red light, top row; shallower water, middle row; deeper water, bottom row) and light leve... حسب Callum Gray (2691769)

الموضوعات:

Calculation algorithm implementing the proposed model. حسب Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. حسب Landry Djopkop Kouanang (17131748)

Sanitized databases using MLHProtector algorithm. حسب Loan T. T. Nguyen (20660789)

"…To address this issue, this work suggests two PPUM algorithms, namely <b>MLHProtector</b> and <b>FMLHProtector</b>, to operate at all abstraction levels in a transaction database to protect them from data mining algorithms. …"

Ambient light and transmitted light comparison diagram. حسب Yuliang Yuan (4478698)

الموضوعات:

Quantifying solution overlap using IOU (dots). حسب Tarun Khajuria (12117309)

الموضوعات:

Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"