Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx حسب Anjan Kumar Pradhan (9386369)

"…A meta-transcriptome approach was undertaken to interrogate 39,756 genes differentially expressed in response to biotic and abiotic stresses in maize were interrogated for prioritization through seven machine learning (ML) models, such as support vector machine (SVM), partial least squares discriminant analysis (PLSDA), k-nearest neighbors (KNN), gradient boosting machine (GBM), random forest (RF), naïve bayes (NB), and decision tree (DT) to predict top-most significant genes for stress conditions. …"

Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx حسب Anjan Kumar Pradhan (9386369)

"…A meta-transcriptome approach was undertaken to interrogate 39,756 genes differentially expressed in response to biotic and abiotic stresses in maize were interrogated for prioritization through seven machine learning (ML) models, such as support vector machine (SVM), partial least squares discriminant analysis (PLSDA), k-nearest neighbors (KNN), gradient boosting machine (GBM), random forest (RF), naïve bayes (NB), and decision tree (DT) to predict top-most significant genes for stress conditions. …"

Details of S-shaped and V-shaped functions. حسب Yan Wei (32168)

"…Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. …"

10-fold cross-validation evaluation of accuracy of animal tracking algorithms. حسب Catalin Mitelut (5587493)

Parameters of the test function. حسب Yiqiong Gao (16698968)

"…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …"

Table_1_Identifying Mild Hepatic Encephalopathy Based on Multi-Layer Modular Algorithm and Machine Learning.DOCX حسب Gaoyan Zhang (450697)

الموضوعات:

LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes حسب Olivier Collier (7444844)

Library of the 55 different classification and regression machine-learning algorithms used by the ensemble predictor SuperLearner (SL.library) in the CBDA 2.0 implementation. حسب Simeone Marino (81051)

الموضوعات:

Flowchart of the clinical decision support system and the interpretable tropical geometry-based fuzzy neural network algorithm. حسب Yufeng Zhang (195768)

Output results based on three algorithms. حسب Yiqiong Gao (16698968)

"…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …"

datasheet1_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.pdf حسب Santiago Hernández-Orozco (5070209)

"…We find and report that 1) machine learning can successfully be performed on a non-smooth surface using algorithmic complexity; 2) that solutions can be found using an algorithmic-probability classifier, establishing a bridge between a fundamentally discrete theory of computability and a fundamentally continuous mathematical theory of optimization methods; 3) a formulation of an algorithmically directed search technique in non-smooth manifolds can be defined and conducted; 4) exploitation techniques and numerical methods for algorithmic search to navigate these discrete non-differentiable spaces can be performed; in application of the (a) identification of generative rules from data observations; (b) solutions to image classification problems more resilient against pixel attacks compared to neural networks; (c) identification of equation parameters from a small data-set in the presence of noise in continuous ODE system problem, (d) classification of Boolean NK networks by (1) network topology, (2) underlying Boolean function, and (3) number of incoming edges.…"

datasheet2_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.zip حسب Santiago Hernández-Orozco (5070209)

"…We find and report that 1) machine learning can successfully be performed on a non-smooth surface using algorithmic complexity; 2) that solutions can be found using an algorithmic-probability classifier, establishing a bridge between a fundamentally discrete theory of computability and a fundamentally continuous mathematical theory of optimization methods; 3) a formulation of an algorithmically directed search technique in non-smooth manifolds can be defined and conducted; 4) exploitation techniques and numerical methods for algorithmic search to navigate these discrete non-differentiable spaces can be performed; in application of the (a) identification of generative rules from data observations; (b) solutions to image classification problems more resilient against pixel attacks compared to neural networks; (c) identification of equation parameters from a small data-set in the presence of noise in continuous ODE system problem, (d) classification of Boolean NK networks by (1) network topology, (2) underlying Boolean function, and (3) number of incoming edges.…"

datasheet1_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.pdf حسب Santiago Hernández-Orozco (5070209)

"…We find and report that 1) machine learning can successfully be performed on a non-smooth surface using algorithmic complexity; 2) that solutions can be found using an algorithmic-probability classifier, establishing a bridge between a fundamentally discrete theory of computability and a fundamentally continuous mathematical theory of optimization methods; 3) a formulation of an algorithmically directed search technique in non-smooth manifolds can be defined and conducted; 4) exploitation techniques and numerical methods for algorithmic search to navigate these discrete non-differentiable spaces can be performed; in application of the (a) identification of generative rules from data observations; (b) solutions to image classification problems more resilient against pixel attacks compared to neural networks; (c) identification of equation parameters from a small data-set in the presence of noise in continuous ODE system problem, (d) classification of Boolean NK networks by (1) network topology, (2) underlying Boolean function, and (3) number of incoming edges.…"

datasheet2_Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.zip حسب Santiago Hernández-Orozco (5070209)

"…We find and report that 1) machine learning can successfully be performed on a non-smooth surface using algorithmic complexity; 2) that solutions can be found using an algorithmic-probability classifier, establishing a bridge between a fundamentally discrete theory of computability and a fundamentally continuous mathematical theory of optimization methods; 3) a formulation of an algorithmically directed search technique in non-smooth manifolds can be defined and conducted; 4) exploitation techniques and numerical methods for algorithmic search to navigate these discrete non-differentiable spaces can be performed; in application of the (a) identification of generative rules from data observations; (b) solutions to image classification problems more resilient against pixel attacks compared to neural networks; (c) identification of equation parameters from a small data-set in the presence of noise in continuous ODE system problem, (d) classification of Boolean NK networks by (1) network topology, (2) underlying Boolean function, and (3) number of incoming edges.…"

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. حسب Gursimran Singh (575288)

الموضوعات:

The results of ICA performed using PyNoetic. حسب Gursimran Singh (575288)

الموضوعات:

Table 1_Machine learning-based gait adaptation dysfunction identification using CMill-based gait data.docx حسب Hang Yang (577653)

"…ML models based on Support Vector Machine, Decision Tree, Multi-layer Perceptron, K-Nearest Neighbors, and AdaCost algorithm were trained to classify individuals with and without GAD. …"

DataSheet1_Detection of Synergistic Interaction on an Additive Scale Between Two Drugs on Abnormal Elevation of Serum Alanine Aminotransferase Using Machine-Learning Algorithms.pdf حسب Hayato Akimoto (3132798)

الموضوعات:

DataSheet2_Detection of Synergistic Interaction on an Additive Scale Between Two Drugs on Abnormal Elevation of Serum Alanine Aminotransferase Using Machine-Learning Algorithms.doc... حسب Hayato Akimoto (3132798)

الموضوعات:

Prediction algorithm. حسب Muhammad Irfan (255476)

"…Finally, it implements the ELPF using an improved method Residual Network (ResNet-152) and the machine-improved Support Vector Machine (SVM) based forecasting engine to forecast the ELP accurately. …"