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114 articles for “Decision Tree”

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Research ArticleOpen accessIn the abstractFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,677 accessesView PDFCite
Research ArticleOpen accessIn the abstractTone Question of Tree Based Context Clustering for Hidden Markov Model Based Thai Speech SynthesisSuphattharachai ChomphanProblem statement: In HMM-based Thai speech synthesis, tone is an important issue that brings about the intelligibility of the synthesized speech. Tone distortion resulted from imbalance of the training data should be appropriately treated. Approach: This study described an HMM-based speech synthesis system for Thai language. In the system, spectrum, pitch and state duration are modeled simultaneously in a unified … …Journal of Computer Science, Vol. 6, Issue 12 · 9 Nov 2010 · 6,823 accessesView PDFCite
Research ArticleOpen accessIn the abstractPattern Trees for Fault-Proneness Detection in Object-Oriented SoftwareRomana Ishrat, Rafat Parveen, Syed I. AhsonProblem statement: This study introduced an application of pattern tree based classification technique in the area of object-oriented software quality estimation. This application explored the fault prediction accuracy of pattern trees. Approach: Similarity measures and fuzzy aggregations employed in the pattern tree technique had been used to generate tree models for fault detection in software modules. Experiments had been performed … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Jul 2010 · 6,953 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Approach in Individual Tree Counting of Nyatoh (Palaquium spp.) Using an Airborne SpectroradiometerKamaruzaman JusoffProblem statement: In Malaysia inadequate data are available to make decisions regarding the sustainable management of Nyatoh (Palaquium spp.). Factual data and estimation of Nyatoh in the lowland dipterocarp forest resources are still lacking or, if available, are not complete, reliable or up to date. The collection and compilation of information and updating of existing data in near real time … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 7,960 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards the Development of Speaker-Dependent and Speaker-Independent Hidden Markov Model-Based Thai Speech SynthesisSuphattharachai ChomphanProblem statement: Tone distortion in Thai languages can deteriorate not only the intelligibility of speech but also its naturalness. Therefore, the correctness of tone must be carefully taken into account in continuous speech synthesis. The preliminary work confronted this problem when applying HMM-based speech synthesis to Thai. Approach: This study presented a study on speaker-dependent and speaker-independent Hidden Markov Model … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 6,928 accessesView PDFCite
Research ArticleOpen accessIn the abstractLong Short-Term Memory Model for Classification of English-PtBR Cross-Lingual Hate SpeechThiago D. Bispo, Hendrik T. Macedo, Flávio de O. Santos et al.Automatic and accurate recognition of hate speech is a difficult job. In addition to the inherent ambiguity of the natural language, deep understanding of the linguistic structure is imperative. Usually, discriminatory discourse does not make use of typical expressions and often abuse of sarcasm. Good knowledge of world and assessment of context are thus highly demanded. Several approaches have been … …Journal of Computer Science, Vol. 15, Issue 10 · 1 Nov 2019 · 7,343 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,796 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransforming Saffron Cultivation With Smart Hydroponics: An Artificial Intelligence of Things Approach to Crops and Nutrients ManagementVivek Raj, Gregory Allen, Ananth Prabhu G., Melwin DsouzaAgriculture is changing with the aid of new technologies, particularly in several Asian countries. This research applies Artificial Intelligence (AI) and the Internet of Things (IoT) to traditional farming, particularly focusing on saffron cultivation using hydroponics. Hydroponics is especially useful as a city grows, because it not only saves space but also nourishes the plants directly through the roots - … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 862 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,853 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,549 accessesView PDFCite