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16 results for “Hyperparameter Tuning”
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Research ArticleOpen accessPhrase in the titleImproved SVM with Hyperparameter Tuning for Fake News DetectionAtcharaporn Nachaithong, Kittipol WisaengIn today’s digital age, accessing information has become effortless. An abundance of resources is available online, from trustworthy news outlets providing factual information to unverified opinions shared by anonymous individuals. With the advent of modern technology, social media platforms have revolutionized interaction and staying informed, providing instant access to news and information related to a wide range of topics. They … …Journal of Computer Science, Vol. 20, Issue 10 · 28 Aug 2024 · 5,636 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,148 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic PatientBiplov Paneru, Bishwash Paneru, Krishna Bikram Shah et al.The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and refined, including Support Vector Machines (SVM), Random Forest, XGBoost, Multi-Layer Perceptron (MLP) and a hybrid model that combines MLP and SVM. To evaluate the durability of the … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,219 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCuckoo Search Optimized Random Forest for Breast Cancer PrognosisPrasad S. Sase, Debabrata Swain, Shailesh KumarBreast cancer remains a major global health concern due to its high mortality rate, particularly when diagnosis occurs at an advanced stage. Accurate and early differentiation between benign and malignant tumors is therefore critical for improving patient outcomes. Conventional diagnostic practices largely depend on manual assessment and clinical expertise, which may lead to subjective variability in decision-making. To overcome this … …Journal of Computer Science, Vol. 22, Issue 1 · 31 Jan 2026 · 2,098 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Attention-Based Stacked Bi-LSTM Model for Automated MultiImage CaptioningPaspula Ravinder, Saravanan SrinivasanIn recent days, the process of medical image captioning is become a prominent field. The distinct characteristics of medical imaging data provide a number of challenges when captioning medical images. Also, the variability in image modalities makes it difficult to generate an effective captioning process. Thus, the proposed study aims to design a novel Multi-image Captioning Hybrid Attention Model to … …Journal of Computer Science, Vol. 21, Issue 4 · 8 Mar 2025 · 5,157 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 403 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite