Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

119 articles for “random sampling”
Set a search alert
Research ArticleOpen accessPhrase in the titleUsing Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity FunctionsLappoon R. TangThe Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 5,481 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleUsing the Spreadsheet to Understand Random Sampling Procedures in Relation to the Central Limit TheoremRamzi Naim NasserIn many statistics courses in colleges and universities, random sampling has not been presented to students through a hands-on and practical approach. This research described a real-life method to random sampling was used as an exercise in the statistics class. The method allowed students to recursively select 5, 10, 20, 30, 40, 50, 60 and 70 samples and list these … …Journal of Mathematics and Statistics, Vol. 4, Issue 3 · 30 Sep 2008 · 6,977 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Systematic Procedure for Square Random Lattice SamplingGirish Chandra, Neeraj TiwariAn attempt has been made in this paper to improve the method 'Square Random Lattice Sampling' by suggesting a systematic procedure for achieving the goals under controls beyond stratification. The estimator of mean and its variance are calculated. Results shows that the relative precision of the proposed procedure increases as size of the latin square and the number of latin … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 20 Jul 2017 · 6,962 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparison Between Selective Sampling and Random Undersampling for Classification of Customer Defection Using Support Vector MachineHeri Kuswanto, Yogi Sarumaha, Hayato OhwadaQuality of a product determines the customer loyalty and it can be measured by conducting a survey. Company ‘X’ that sells three kinds of product (low, medium and high price) collected very large dataset through an online survey and recorded customer defection and their characteristic. The measured variables are Update Accumulation, Product Price, Customer Type, Delivery Status and Customer Defection. … …Journal of Computer Science, Vol. 13, Issue 8 · 16 Aug 2017 · 7,263 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModified Ratio-Type Estimators of the Mean using Extreme Ranked Set SamplingAmer Ibrahim Al-Omari, Khalifa Jaber, Ahmad Al-OmariModified ratio-type estimators of the population mean were suggested using the first or third quartiles of the auxiliary variable based on Simple Random Sampling (SRS) and Extreme Ranked Set Sampling (ERSS) methods. It was found that, the ERSS was more efficient than the SRS based on the same sample size. Also, the ERSS involving the first quartile was superior to … …Journal of Mathematics and Statistics, Vol. 4, Issue 3 · 30 Sep 2008 · 7,362 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPercentile Double Ranked Set SamplingAmer Ibrahim Al-Omari, Khalifa H. JaberIn this paper, percentile double ranked set sampling (PDRSS) method is suggested for estimating the population mean. The PDRSS method is compared with the simple random sampling (SRS), ranked set sampling (RSS), median ranked set sampling (MRSS) and the extreme ranked set sampling (ERSS) methods. When the underlying distribution is symmetric, it turns out that PDRSS produce unbiased estimators of … …Journal of Mathematics and Statistics, Vol. 4, Issue 1 · 31 Mar 2008 · 7,411 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMultistage Median Ranked Set Sampling for Estimating the Population MedianAbdul Aziz Jemain, Amer Al-Omari, Kamarulzaman IbrahimWe modify RSS to come up with new sampling method, namely, Multistage Median Ranked Set Sampling (MMRSS). The MMRSS was suggested for estimating the population median and to increase the efficiency of the estimator for specific value of the sample size. The MMRSS was compared to the Simple Random Sampling (SRS), Ranked Set Sampling (RSS) and Median Ranked Set Sampling … …Journal of Mathematics and Statistics, Vol. 3, Issue 2 · 30 Jun 2007 · 7,143 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRandomized Response Procedure for the Estimation of the Population Ratio using Ranked Set SamplingAgustin Santiago, Carlos N. Bouza, J. Maclovio Sautto, Amer Ibrahim Al-OmariIn this study we deal with the estimation of the population ratio, when a Randomized Response (RR) procedure is used for collecting responses and Ranked Set Sampling (RSS) is the selection method. The variances of the suggested estimators are calculated. Comparisons between different estimators are presented. …Journal of Mathematics and Statistics, Vol. 12, Issue 2 · 27 Apr 2016 · 7,396 accessesView PDFCite
Research ArticleOpen accessIn the keywordsStochastic Estimator-Based Wireless Traffic Control SchemesFrancis Joseph Ogwu, Mohammad Talib, Ganiyu Adesola AderounmuRecent works on Available Bit Rate (ABR) traffic control have generated efficient control schemes for ABR traffic on Asynchronous Transfer Mode (ATM) network. This study examines the improved performance envisaged if these control schemes adjust dynamically to the varying ABR bandwidth capacity in a stochastic manner instead of conventional deterministic approach .The performance difference between setting explicit rate deterministically for … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 7,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite