Search Results - (( pattern mining algorithm ) OR ( between learning algorithms ))
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance
Published 2003“…These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Mining Indirect Least Association Rule from Students’ Examination Datasets
Published 2014“…Therefore, in this paper we applied our novel algorithm called Mining Lease Association Rule (MILAR) and our measure called Critical Relative Support (CRS) to mine the indirect least association rule from the students’ examination datasets. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Classification of cervical cancer using random forest
Published 2022“…Model evaluation has been conducted to identify the robust data mining algorithm in the prediction of cervical cancer risk. …”
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Mining Indirect Least Association Rule from Students' Examination Datasets
Published 2014“…Therefore, in this paper we applied our novel algorithm called Mining Lease Association Rule (MILAR) and our measure called Critical Relative Support (CRS) to mine the indirect least association rule from the students' examination datasets. …”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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13
Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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17
DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database
Published 2012“…Nowadays, FP-Growth is one of the famous and benchmarked algorithms to mine the frequent patterns from FP-Tree data structure. …”
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Algorithms for frequent itemset mining: a literature review
Published 2018“…This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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A numerical method for frequent pattern mining
Published 2009“…Frequent pattern mining is one of the active research themes in data mining. …”
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