Search Results - (( data representation learning algorithm ) OR ( java application learning algorithm ))
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Dimensionality reduction in data summarization approach to learning relational data
Published 2013“…Based on the experimental results, the DARA algorithm is proven to be very effective in learning relational data. …”
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Book -
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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Unsupervised learning of image data using generative adversarial network
Published 2020“…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
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Proceedings -
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…The Multimodal Transformer Fusion (MMTF) model uses the cross-modal attention mechanisms to combine these streams of data to produce unified emotional representations. …”
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Learning representations of network traffic using deep neural networks for network anomaly detection: A perspective towards oil and gas it infrastructures
Published 2020“…In this study we propose, implement and evaluate use of Deep learning to learn effective Network data representations from raw network traffic to develop data driven anomaly detection systems. …”
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Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space
Published 2021“…Thus, subspace learning techniques are employed to reduce the dimensionality of the data prior to employing other learning algorithms. …”
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Implementation of hashed cryptography algorithm based on cryptography message syntax
Published 2019“…The coding is designed in such a way that there is a malicious attack to destroy the data. The system will automatically protect data and thus retrieve data at the end of the system. …”
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Document classification based on kNN algorithm by term vector space reduction
Published 2023Conference Paper -
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan
Published 2024“…Text preprocessing ensures consistent data representation and facilitates validation. The Machine Learning algorithm, comprising Random Forest, Linear Regression, XGBoost, SVM, and Stacking Ensemble, is embedded in the system for job position predictions based on the analysed data. …”
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Localized deep extreme learning machines for efficient RGB-D object recognition
Published 2015“…Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks. The former lack representation ability while the latter require large amounts of training data and learning time. …”
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Proceeding Paper -
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The importance of data classification using machine learning methods in microarray data
Published 2021“…One of these challenges involves high dimensional data that are redundant, irrelevant, and noisy. To alleviate this problem, this representation should be simplified. …”
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Applying learning to filter text
Published 2005“…The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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Conference or Workshop Item -
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Central to this process is the representation of words through vectors for computational interpretation. …”
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Contrastive Self-Supervised Learning for Image Classification
Published 2021“…Through self-supervised learning, pretraining of the model can be conducted without any human-labelled data and the model can learn from the data itself. …”
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Final Year Project / Dissertation / Thesis -
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Conference or Workshop Item -
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…It can pose difficulties for standard machine learning document representations because of the short length coupled with their noisy nature. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection
Published 2024“…To address this challenge, feature selection (FS) is conducted during the data pre-processing phase with the objective of enhancing the learning accuracy and efficiency of the model. …”
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