Search Results - (( variable interactions tree algorithm ) OR ( java applications usage algorithm ))
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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2
An Effective Fast Searching Algorithm for Internet Crawling Usage
Published 2016“…The search algorithm is a crucial part in any internet applications. …”
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Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique
Published 2017“…Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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Mining Sequential Patterns using I-PrefixSpan
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. …”
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A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
Published 2018“…The behaviors and interactions among the stocks in Bursa Malaysia are then determined by using the Forest of all possible minimum spanning trees. …”
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8
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.…”
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