FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2945819472> ?p ?o ?g. }

• W2945819472 endingPage "112" @default.
• W2945819472 startingPage "89" @default.
• W2945819472 abstract "Ensemble methods consist of combining more than one single technique to solve the same task. This approach was designed to overcome the weaknesses of single techniques and consolidate their strengths. Ensemble methods are now widely used to carry out prediction tasks (e.g. classification and regression) in several fields, including that of bioinformatics. Researchers have particularly begun to employ ensemble techniques to improve research into breast cancer, as this is the most frequent type of cancer and accounts for most of the deaths among women.The goal of this study is to analyse the state of the art in ensemble classification methods when applied to breast cancer as regards 9 aspects: publication venues, medical tasks tackled, empirical and research types adopted, types of ensembles proposed, single techniques used to construct the ensembles, validation framework adopted to evaluate the proposed ensembles, tools used to build the ensembles, and optimization methods used for the single techniques. This paper was undertaken as a systematic mapping study.A total of 193 papers that were published from the year 2000 onwards, were selected from four online databases: IEEE Xplore, ACM digital library, Scopus and PubMed. This study found that of the six medical tasks that exist, the diagnosis medical task was that most frequently researched, and that the experiment-based empirical type and evaluation-based research type were the most dominant approaches adopted in the selected studies. The homogeneous type was that most widely used to perform the classification task. With regard to single techniques, this mapping study found that decision trees, support vector machines and artificial neural networks were those most frequently adopted to build ensemble classifiers. In the case of the evaluation framework, the Wisconsin Breast Cancer dataset was the most frequently used by researchers to perform their experiments, while the most noticeable validation method was k-fold cross-validation. Several tools are available to perform experiments related to ensemble classification methods, such as Weka and R Software. Few researchers took into account the optimisation of the single technique of which their proposed ensemble was composed, while the grid search method was that most frequently adopted to tune the parameter settings of a single classifier.This paper reports an in-depth study of the application of ensemble methods as regards breast cancer. Our results show that there are several gaps and issues and we, therefore, provide researchers in the field of breast cancer research with recommendations. Moreover, after analysing the papers found in this systematic mapping study, we discovered that the majority report positive results concerning the accuracy of ensemble classifiers when compared to the single classifiers. In order to aggregate the evidence reported in literature, it will, therefore, be necessary to perform a systematic literature review and meta-analysis in which an in-depth analysis could be conducted so as to confirm the superiority of ensemble classifiers over the classical techniques." @default.
• W2945819472 created "2019-05-29" @default.
• W2945819472 creator A5000218612 @default.
• W2945819472 creator A5021486420 @default.
• W2945819472 creator A5040944378 @default.
• W2945819472 creator A5045175946 @default.
• W2945819472 creator A5066735709 @default.
• W2945819472 date "2019-08-01" @default.
• W2945819472 modified "2023-10-17" @default.
• W2945819472 title "Reviewing ensemble classification methods in breast cancer" @default.
• W2945819472 cites W1191482210 @default.
• W2945819472 cites W1516835213 @default.
• W2945819472 cites W1534477342 @default.
• W2945819472 cites W1791903561 @default.
• W2945819472 cites W1915129189 @default.
• W2945819472 cites W1968339465 @default.
• W2945819472 cites W1970826986 @default.
• W2945819472 cites W1982067074 @default.
• W2945819472 cites W1983578130 @default.
• W2945819472 cites W1999625228 @default.
• W2945819472 cites W1999798506 @default.
• W2945819472 cites W2000792642 @default.
• W2945819472 cites W2005827916 @default.
• W2945819472 cites W2010941383 @default.
• W2945819472 cites W2012035409 @default.
• W2945819472 cites W2019591452 @default.
• W2945819472 cites W2031114303 @default.
• W2945819472 cites W2033803508 @default.
• W2945819472 cites W2037664399 @default.
• W2945819472 cites W2041239012 @default.
• W2945819472 cites W2043765927 @default.
• W2945819472 cites W2057521255 @default.
• W2945819472 cites W2059704512 @default.
• W2945819472 cites W2061119986 @default.
• W2945819472 cites W2069484894 @default.
• W2945819472 cites W2087264237 @default.
• W2945819472 cites W2097802970 @default.
• W2945819472 cites W2106390255 @default.
• W2945819472 cites W2107641306 @default.
• W2945819472 cites W2113242816 @default.
• W2945819472 cites W2115629999 @default.
• W2945819472 cites W2116209708 @default.
• W2945819472 cites W2116825089 @default.
• W2945819472 cites W2123822128 @default.
• W2945819472 cites W2126414602 @default.
• W2945819472 cites W2128306614 @default.
• W2945819472 cites W2128961774 @default.
• W2945819472 cites W2129560785 @default.
• W2945819472 cites W2133647570 @default.
• W2945819472 cites W2135293965 @default.
• W2945819472 cites W2146528527 @default.
• W2945819472 cites W2148001258 @default.
• W2945819472 cites W2155487617 @default.
• W2945819472 cites W2159578113 @default.
• W2945819472 cites W2162259428 @default.
• W2945819472 cites W2164959040 @default.
• W2945819472 cites W2168960022 @default.
• W2945819472 cites W2170166909 @default.
• W2945819472 cites W2170341854 @default.
• W2945819472 cites W2204950599 @default.
• W2945819472 cites W2205836001 @default.
• W2945819472 cites W2219498772 @default.
• W2945819472 cites W2229512561 @default.
• W2945819472 cites W2249882699 @default.
• W2945819472 cites W2262790950 @default.
• W2945819472 cites W2262813534 @default.
• W2945819472 cites W2289087065 @default.
• W2945819472 cites W2290687990 @default.
• W2945819472 cites W2323062188 @default.
• W2945819472 cites W2327913792 @default.
• W2945819472 cites W2332381255 @default.
• W2945819472 cites W2391474792 @default.
• W2945819472 cites W2398552133 @default.
• W2945819472 cites W2479132886 @default.
• W2945819472 cites W2516246192 @default.
• W2945819472 cites W2551893789 @default.
• W2945819472 cites W2552678868 @default.
• W2945819472 cites W2559937118 @default.
• W2945819472 cites W2593591744 @default.
• W2945819472 cites W2595035151 @default.
• W2945819472 cites W2724532147 @default.
• W2945819472 cites W2740804519 @default.
• W2945819472 cites W2743635406 @default.
• W2945819472 cites W2750832676 @default.
• W2945819472 cites W2761168727 @default.
• W2945819472 cites W2773381949 @default.
• W2945819472 cites W2781900029 @default.
• W2945819472 cites W2782881162 @default.
• W2945819472 cites W2791879663 @default.
• W2945819472 cites W2791932061 @default.
• W2945819472 cites W2792567125 @default.
• W2945819472 cites W2792982570 @default.
• W2945819472 cites W2797080809 @default.
• W2945819472 cites W2801584820 @default.
• W2945819472 cites W2801929034 @default.
• W2945819472 cites W2806245972 @default.
• W2945819472 cites W2885669402 @default.
• W2945819472 cites W2887723631 @default.

• next