Feature Selection for Microarray Data Classification Using Hybrid Information Gain and a Modified Binary Krill Herd Algorithm حسب Ge Zhang (112487)

"…A pre-screening method of feature ranking which is based on information gain (IG) and an improved binary krill herd (MBKH) algorithm are integrated in this strategy. …"

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

"…Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"

A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Propo... حسب Zachary P. Neal (9946331)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب Jianfang Cao (1881379)

"…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …"

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

"…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"

Visual representation of the combination of feature extraction approaches employed and classification algorithms to identify stomata. حسب Alexandre H. Aono (11603934)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<b>(E)</b> Starting from the interaction at the top of <i>I</i>_<i>δ</i>, <i>hi</i>PRS constructs <i>I</i>_<i>K</i>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …"

Classification baseline performance. حسب Doaa Sami Khafaga (21463870)

"…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …"

Feature selection results. حسب Doaa Sami Khafaga (21463870)

"…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …"

ANOVA test result. حسب Doaa Sami Khafaga (21463870)

"…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …"

Summary of literature review. حسب Doaa Sami Khafaga (21463870)

"…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …"

Application of ABC SMC to the fitting of the binary flip with cusp model. حسب Elena Camacho-Aguilar (10906327)

State-of-the-art methods for X-ray image classification. Summarised in terms of the classifier, preprocessing, and features extraction used and their performance using the differen... حسب Antonio Quintero-Rincón (21087716)

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

"…We used five machine-learning base algorithms to construct the classifiers. This study trained and validated the models to classify the AXLs eyes based on binary (AXL < or > 26 mm) and multiclass (AXL < 22 mm, between 22 and 26 mm, and > 26 mm) classifications.…"

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

"…We used five machine-learning base algorithms to construct the classifiers. This study trained and validated the models to classify the AXLs eyes based on binary (AXL < or > 26 mm) and multiclass (AXL < 22 mm, between 22 and 26 mm, and > 26 mm) classifications.…"

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

Optimal Timings Codebook.xlsx حسب Emma Spillane (11249121)