Search Results - (( model evaluation case algorithm ) OR ( data classification _ algorithm ))*

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

“…The SVMAK model outperformed these models, and in some cases improved the accuracy of the minority class classification. …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…To evaluate the efficacy of the models, publicly available financial and credit card data sets are evaluated. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

“…This project implements the Naive Bayes algorithm as the classification algorithm. The collected data from LinkedIn profiles then undergoes data preprocessing. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…It was shown that up to 95.02% of the trained Random Forest Model could be classified, indicating that the established framework is viable for pallet classification. …”
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Deep learning algorithm and IoT based system for Photovoltaic (PV) defect images classification by Mazlan, Nurul Atikah

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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

“…Benchmarking; Decision support systems; Hospital data processing; Intensive care units; Patient treatment; Trees (mathematics); Blood glucose measurements; Classification precision; Discretization algorithms; Discretizations; Glycemic control; Performance prediction; Structure-learning; Variable selection; Bayesian networks…”

Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset by Abd Rahman, M. Hafiz Fazren, Wan Salim, Wan Wardatul Amani, Abd-Wahab, Firdaus

“…In this case, data mining and machine learning applications prove to be a powerful tool in transforming data into a meaningful knowledge. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. The LiDARderived data, orthophotos and textural features significantly affected the classification results. …”
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Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring by Abualsaud, Khalid, Mahmuddin, Massudi, Hussein, Ramy, Mohamed, Amr

“…DCT is combined with the best basis function neural networks for EEG signals classification.Extensive experimental work is conducted, utilizing four classification models.The obtained results show an improvement in classification accuracies and an optimal classification rate of about 95% is achieved when using NN classifier at 85% of CR in the case of no SNR value.The satisfying results demonstrate the effect of efficient compression on maximizing the sensor lifetime without affecting the application’s accuracy.…”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”

Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum by Wardhana, Mohammad Hadyan

“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

“…Data sets for this research consist of two sets integration data of air quality data and macroeconomic data of the cross-country data of World Development Indicator 2003 (WDI 2003), and from www.nationmaster.com. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…Data arrives from operational field in a stream model and similarity-based classification algorithms must identify them with acceptable performance. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…Since the 1960s, many algorithms for data classification have been proposed. …”
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