بدائل البحث:
learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data learning » deep learning (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data learning » deep learning (توسيع البحث)
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101
Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
منشور في 2023"…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …"
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102
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103
Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
منشور في 2022"…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. …"
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106
Fuzzy genetic algorithm for floorplanning
منشور في 2020"…Genetic algorithms (GAs) have been found to be very effective in solving numerous optimization problems, especially those with many (possibly) conflicting and noisy objectives. …"
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107
Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
منشور في 2024الموضوعات: -
108
A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network
منشور في 2020"…The data is finally classified as either ransomware or goodware using the learning methodologies. …"
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109
Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
منشور في 2024"…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …"
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
منشور في 2019"…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …"
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112
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
منشور في 2025"…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …"
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
منشور في 2021"…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…"
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
منشور في 2020"…However, high dimensional data present a significant challenge for machine learning techniques. …"
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117
Boosting the visibility of services in microservice architecture
منشور في 2023"…These assessments can be performed by means of a live health-check service, or, alternatively, by making a prediction of the current state of affairs with the application of machine learning-based approaches. In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …"
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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques
منشور في 2024"…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …"
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120
Unsupervised outlier detection in multidimensional data
منشور في 2022"…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …"