Search alternatives:
process optimization » model optimization (Expand Search)
dense optimization » dose optimization (Expand Search), phase optimization (Expand Search), descent optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary from » diary from (Expand Search), library from (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
from dense » from diverse (Expand Search), from disease (Expand Search), from density (Expand Search)
process optimization » model optimization (Expand Search)
dense optimization » dose optimization (Expand Search), phase optimization (Expand Search), descent optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary from » diary from (Expand Search), library from (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
from dense » from diverse (Expand Search), from disease (Expand Search), from density (Expand Search)
-
81
-
82
-
83
-
84
GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
-
85
The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
-
86
Confusion matrix.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
-
87
Parameter settings.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
-
88
Thesis-RAMIS-Figs_Slides
Published 2024“…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
-
89
-
90
PathOlOgics_RBCs Python Scripts.zip
Published 2023“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”
-
91
Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…This result reflects the effectiveness of the algorithm, which provides a basis for the effective analysis and processing of image big data.…”
-
92
Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf
Published 2019“…The Digital Annealer's algorithm is currently based on simulated annealing; however, it differs from it in its utilization of an efficient parallel-trial scheme and a dynamic escape mechanism. …”
-
93
Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
Published 2024“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
-
94
-
95
-
96
Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…<p>Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature data to obtain a lower price, incurring certain manipulation costs. …”
-
97
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
-
98
-
99
Seed mix selection model
Published 2022“…The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …”
-
100
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”