Search Results - (( re evaluation step algorithm ) OR ( label classification mining algorithm ))

Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

“…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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A negotiation algorithm for decision-making in the construction domain by Idrus A., Mahmoud M.A., Ahmad M.S., Yahya A., Husen H.

Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer by Hilo, Ali Kareem, Abu Talib, Abd Rahim, Iborra, Antonio Acosta, Hameed Sultan, Mohamed Thariq, Abdul Hamid, Mohd Faisal

“…Combining the corrugated wall with backward-facing step enhanced the Nusselt number (Nu) up to 62% at Re = 5000. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Nanofluid flow and heat transfer in corrugated backward-facing step channel using ethylene glycol as based fluid by Hilo, Al Behadili Ali Kareem

“…Combined the backward-facing step with corrugated wall enhanced the Nusselt number (Nu) up to 62% at Re = 5,000. …”
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ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“… • All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided…”
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Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Re: Gen - web-based resume generator with content recommender for it job field / Nurul Syahmina Mohd Khairuddin … [et al.] by Mohd Khairuddin, Nurul Syahmina, Ahmadon, Fadzlin, Hashim, Madihah Hannani, Mohd Vauxhall, Nur Ain Emylia

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Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

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ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj by Bryan Raj , Peter Jabaraj

“…Moreover, two improvised clustering techniques are introduced to reduce the energy overhead cost from the re-clustering process. The performance of aHSSOGA is evaluated based on average residual energy, network lifetime, total re-clustering occurrence, total data delivery, network throughput and end-to-end delay metrics. …”
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