Search Results - (( java application use algorithm ) OR ( level classification learning algorithm ))

Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…The blockage of the pump inlet could result in cavitation or mechanical parts breakdown which would increase the maintenance cost. Machine Learning is one of the ways as a preventive method by applying the data collected from the clogging experiment in the vibration lab to build up a machine learning model for classification of flow blockage levels in the centrifugal pump. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”

Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Next generation insect taxonomic classification by comparing different deep learning algorithms by Song-Quan Ong, Suhaila Ab. Hamid

“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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Classification and prediction of obesity levels among subjects in Colombia, Peru, and Mexico using unsupervised and supervised learning by Suhaila, Bahrom, Anuar, Ab Rani, Aisyah Amalina, Mohd Noor

“…Supervised learning algorithms like logistic regression, random forest, and adaboost classifier predict obesity levels based on labelled datasets, with random forest exhibiting superior performance. …”
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Prediction of the level of air pollution during wildfires using machine learning classification methods by Khalid, Syed Mohammed, Hassan, Raini

“…Recent studies indicate that data retrieved from remote sensing satellites is now an emerging alternative for air quality prediction at the ground level. Hence, this research aims to use satellite-based data to predict the air quality of East Malaysian cities with the help of different Machine Learning classification algorithms. …”
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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

“…This study will ultimately contribute to society's development with improved robust machine learning algorithm for binary classification.…”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Classification for the fruit maturity using Neural Network by Mohamad Naeem Hussien

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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…The model was validated by predicting ripeness level for another FFB reflectance dataset. The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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