Search Results - (( data selection methods algorithm ) OR ( variables selection method algorithm ))

Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

“…Moreover, selecting the relevant variables when fitting the regression model is critical. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. This research compares three different methods for extracting features from fruit images to determine which method yields the highest accuracy for fruit classification. …”
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Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

“…In the real data simulation, both methods obtained the same model structure whereas in simulated data modelling, only DMA was able to select the correct model structure. …”
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Feature selection methods for optimizing clinicopathologic input variables in oral cancer prognosis by Chang, S.W., Kareem, S.A., Kallarakkal, A.F., Merican, A.F., Abraham, M.T., Zain, R.B.

“…In this research, we demonstrated the use of feature selection methods to select a subset of variables that is highly predictive of oral cancer prognosis. …”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

“…The empirical results for both algorithms performed well as compared to other models selection procedures, particularly using WQI data where the sample size is bigger and has good quality data. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…This study utilizes genetic algorithms based upon the medoid rather than the mean as a centroid-selection schema to improve the clustering efficiency. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier by Hassan, Raini, Taha Alshaikhli, Imad Fakhri, Ahmad, Salmiah

“…As in the previous work, this work is particularly interested in ISA methods that can manipulate synaptic weights; namely Connection Weights (CW) and Garson’s Algorithm (GA), and the classifier selected is Evolving Fuzzy Neural Networks (EFuNNs). …”
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An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration by Momeni, M., Hosseini, S.J., Ridha, S., Laruccia, M.B., Liu, X.

“…This paper discusses bit selection by employing a method of combining Artificial Neural Network (ANN) and the computation of Genetic Algorithm (GA). …”
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. This involves analyzing 11 sociodemographic and anthropometric variables within a dataset of 113 prospective athletes, encompassing both numerical and categorical data. …”
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