Search Results - machine learning problems

Mental health prediction using machine learning: taxonomy,applications, and challenges by Jetli Chung, Jason Teo

“…The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. )is paper presents a recent systematic review of machine learning approaches in predicting mental health problems. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…Besides, concept drift problem in on-line learning model is solved by Drift Detection Machine (DDM). …”
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Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate by Sallau, Mullah Nanlir

“…To solve the identified research gaps from the vantage point of a machine learning researcher, the problem was modelled as a text classification task. …”
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A machine learning approach to tourism recommendations system by Chia, An

“…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. The main problem encountered when developing a powerful recommendation system is cold start problem, data sparsity and scalability problems. …”
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A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”

Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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Systematic review of using machine learning in imputing missing values by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Che Ani, Zafienas, A. Jabar, Marzanah, Bukar, Umar Ali, Devaraj, Navin Kumar, Muda, Ahmad Sobri, Tharek, Anas, Omar, Noritah, Mohd Jaya, Mohd Izham

“…Novel proposed machine learning approaches used for data imputation are analyzed and summarized to assist researchers in selecting a proper machine learning method based on several factors and settings. …”
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Machine learning for all : Practical steps using MATLAB by Abdullah, Abdul Rahim, Shair, Ezreen Farina, Kandaya, Shaarmila, Rahman, Kazi Ashikur

“…This book, Machine Learning for All: Practical Steps Using Matlab, is written for anyone who wants to learn how to apply machine learning using MATLAB. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

“…In this paper, the performance of three machine learning classifiers (K-Nearest Neighbors (KNN), Decision Tree, and Bayesian Networks) are compared in terms of data imputation accuracy. …”
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Lightweight block cipher security evaluation based on machine learning classifiers and active s-boxes by Lee T.R., Teh J.S., Jamil N., Yan J.L.S., Chen J.

Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction by Masrom, S., Baharun, N., Razi, N.F.M., Rahman, R.A., Abd Rahman, A.S.

“…Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. By comparing the magnitude of change of the R squared values before and after the use of PSO feature selection, the result showed that the automated features selection has improved the results of all the machine learning algorithms mainly in the linear-based machine learning (Linear Regression, Lasso, Ridge). …”
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Single classifer vs. ensemble machine learning approaches for mental health prediction by Jetli Chung, Jason Teo

“…One of the promising approaches to achieving fully automated computer-based approaches for predicting mental health problems is via machine learning. As such, this study aims to empirically evaluate several popular machine learning algorithms in classifying and predicting mental health problems based on a given data set, both from a single classifier approach as well as an ensemble machine learning approach. …”
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Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation by Sivarao, Subramonian

“…The researchers conducted the prediction of C02 laser cut quality to obtain singleton output using machine learning techniques. The researchers investigated a problem solving scenario for a metal cutting industry which faces some problems in determining the end quality final part considering several real life machining scenarios with some expert knowledge input from the industry and machine technology features. …”
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Systematic review of using machine learning in imputing missing values by Alabadla, Mustafa, Fatimah, Sidi, Iskandar, Ishak, Hamidah D., Ibrahim, Lilly Suriani, Affendey, Zafienas, Che Ani, A. Jabar, Marzanah Ab, Bukar, Umar Ali, Devaraj, Navin Kumar, Ahmad Sobri, Muda, Tharek, Anas, Noritah, Omar, Mohd Izham, Mohd Jaya

“…Novel proposed machine learning approaches used for data imputation are analyzed and summarized to assist researchers in selecting a proper machine learning method based on several factors and settings. …”
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Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

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Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

“…However, the functionality of existed and combined visual analytics tech- niques is not sufficient to visualized and interpreted the output of machine learning operation. Other visual analytic techniques faced the same problem, unreliability to produce strong reason on the output when working with com- plex machine learning models. …”
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Propose a New Machine Learning Algorithm based on Cancer Diagnosis by Ali, Mohammed Hasan, Kohbalan, Moorthy, Anad, Mohammed Morad, Mohammed, Mohammed Abdulameer

“…There are many machine learning algorithms proposed for multi-category classification problems in the cancer diagnosis area. …”
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