A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Smart Manufacturing through Machine Learning: A Review, Perspective, and Future Directions to the Machining Industry by A. S. Rajesh, M. S. Prabhuswamy, Srinivasan Krishnasamy

“…The current paper presents a comprehensive survey and summary of different machine learning algorithms which are being employed in various traditional and nontraditional machining processes, and also, an outlook of the manufacturing paradigm is presented. …”
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A multi-chroma format cascaded coding method for full-chroma image in AVS2 by Liping ZHAO, Tao LIN, Kailun ZHOU, Keli HU, Chunmei LIN

“…In the second generation of audio video coding standard (AVS2),a multi-chroma format cascaded coding method (MCFCC) for full-chroma (4:4:4 sampling format) images coding was proposed.The MCFCC algorithm firstly converts the 4:4:4 sampling format image into 4:2:0 sampling format image,then the 4:2:0 sampling format image was processed by 4:2:0 sampling format intra prediction,transform,quantization,inverse quantization,inverse transform,entropy coding and a weighted 4:4:4 sampling format distortion calculation method in the rate-distortion optimization process,finally 4:4:4 sampling format in-loop filtering and offset algorithms were applied to the 4:4:4 sampling format image after up sampling.The experimental results show that,for full-chroma natural images,the MCFCC algorithm achieves higher coding efficiency at very low additional encoding complexity and very low additional design and implementation cost.…”
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A Gaussian Process Latent Variable Model for Subspace Clustering by Shangfang Li

“…Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. …”
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Modularized Learning for Hate Speech Detection in Korean: Integrating Emotions and Multi-Faceted Attributes by Hyeun Jeong Min

“…Built on pre-trained Korean language models, our framework extracts features related to emotion, multiple attributes, and similarity, and then employs a classifier for final prediction. Experimental results demonstrate that our proposed method outperforms existing algorithms by achieving a higher f1-score in hate speech recognition.…”
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A Framework for Determining the Big Five Personality Traits Using Machine Learning Classification through Graphology by null Samsuryadi, Rudi Kurniawan, Julian Supardi, null Sukemi, Fatma Susilawati Mohamad

“…These results indicated that the proposed framework can be well applied to predict the personality of the Big Five model through handwriting analysis features.…”
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Teaching deep networks to see shape: Lessons from a simplified visual world. by Christian Jarvers, Heiko Neumann

“…This suggests that different learning algorithms with sparser, more local weight changes are required to make networks more sensitive to shape and improve their capability to describe human vision.…”
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The influence of eye model parameter variations on simulated eye-tracking outcomes by Joshua Fischer, David van den Heever, Johan van der Merwe

“…The outcomes showed that variations in anterior corneal asphericity significantly influence simulated eye-tracking outcomes of both interpolation and model-based gaze estimation algorithms. Other, more commonly varied parameters such as the corneal radius of curvature and foveal offset angle had little influence on simulated outcomes.  …”
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Dual branch guided contrastive learning for unsupervised pedestrian re-identification by REN Hangjia, LIANG Fengmei

“…The current unsupervised pedestrian re-identification algorithms using residual networks can only extract rough global features, but it can’t adequately reflect subtle local features. …”
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Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. …”
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Neural mechanisms for the attention-mediated propagation of conceptual information in the human brain. by David Acunzo, Damiano Grignolio, Clayton Hickey

“…However, neuroscientific investigation has focused closely on the identification of the systems and algorithms that support attentional control or that instantiate the effect of attention on sensation and perception. …”
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The use of web resources for metabolomics in horticultural crops by Esra Karakas, Mustafa Bulut, Alisdair R. Fernie

“…Moreover, the application of machine learning algorithms to these web resources has further optimized data interpretation, enabling more accurate prediction of metabolic profiles. …”
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Dynamic Simulation and Comprehensive Quantitative Evaluation of Rural Tourism Core Competitiveness Based on Neural Network by Shiyuan Gan

“…This paper first designs the neural network algorithm model, then analyzes the dynamic simulation model and comprehensive quantitative analysis, and then uses the artificial neural network algorithm to analyze and predict the core competitiveness of rural tourism. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). …”
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Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features by Yanping Yang, Jiacheng Shen, Sulan Wei, Maosong Ye, Xing Zhao, Jian Zhou, Lin Tong, Jie Hu, Yuanlin Song, Shengdi Wu, Nuo Xu

“…The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. …”
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Clinical utility of artificial intelligence–augmented endobronchial ultrasound elastography in lymph node staging for lung cancerCentral MessagePerspective by Yogita S. Patel, BSc, Anthony A. Gatti, PhD, Forough Farrokhyar, MPhil, PhD, Feng Xie, PhD, Waël C. Hanna, MDCM, MBA

“…NeuralSeg was able to predict 98 of 143 true negatives and 34 of 44 true positives, resulting in an overall accuracy of 70.59% (95% CI, 63.50-77.01), sensitivity of 43.04% (95% CI, 31.94-54.67), specificity of 90.74% (95% CI, 83.63-95.47), positive predictive value of 77.27% (95% CI, 64.13-86.60), negative predictive value of 68.53% (95% CI, 64.05-72.70), and area under the curve of 0.820 (95% CI, 0.758-0.883). …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles by Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai

“…Our analyses revealed that the Random Forest algorithm exhibited the highest predictive accuracy, with AUC values of 0.809 for kidney stones, 0.99 for ureter stones, and 0.775 for multiple location stones. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Among the ten models tested, the LightGBM algorithm exhibited superior performance, with an AUC of 0.853 in the test cohort. …”
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Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling by Song Liu, Lisheng Yang, Shizhong Yang, Qingping Jiang, Haowei Wu

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