Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Computing the centerline from a binary segmentation. by Patrick D. McClanahan (2385076)

Comparison between Att-RethinkNet based on LSTM and SRN algorithms. by Ran Su (1437445)

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

Subjects: “…Genetics…”

Implementation of Adaptive Genetic Algorithm for classification problems by Dr.E.N. Ganesh (12315038)

“…<p>Genetic algorithms are one of the most</p> <p>commonly used approaches in data mining. …”

Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

The maximum accuracy (lowest error rate) with the least number of ANOVA-ranked genes achieved by different feature filtering methods and classification algorithms refined by SIRRFE... by Song Cui (553627)

(a) Sample architecture of the deep neural network, which consists of 4 layers including input and output (b) Representation of weights of the deep neural network presented in a pa... by De Sheng Fu (19106192)

ROC curves of Att-RethinkNet using LSTM and SRN algorithms on liver data (a) and kidney data (b). by Ran Su (1437445)

Comparison of methods on the datasets described in previous sections. by Dillion M. Fox (4043159)

Subjects:

Fig 2 - by Dillion M. Fox (4043159)

Subjects:

Replica Exchange Monte Carlo (REMC) and Quantum Computing algorithms were tested on systems containing more than 45 stems, which exceeds the practical limit of what can be solved w... by Dillion M. Fox (4043159)

Subjects:

Fig 1 - by Dillion M. Fox (4043159)

Subjects:

Image4_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image1_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image2_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image3_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Data_Sheet_2_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx by Hao-Chun Lu (12965318)

Data_Sheet_1_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx by Hao-Chun Lu (12965318)