Tree‐Based Methods and Decision Trees

Galimberti, Giuliano; Soffritti, Gabriele

doi:10.1002/9781119961154.ch15

Cited by 5 publications

(5 citation statements)

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“…Such concerns call for a more objective method to classify the participants into LSC and HSC groups. In this research, we used the decision tree approach, which is a statistical method at analyzing multivariate data (Lafond et al, 2009 ; Galimberti and Soffritti, 2011 ; Brandmaier et al, 2013 ). This approach has been mainly used in medicine and biology and is now being applied in psychological research, among other applications to classify subjects into low and high groups (Kopiez et al, 2006 ; Lafond et al, 2009 ; Strobl et al, 2009 ).…”

Section: Methodsmentioning

confidence: 99%

“…A decision tree attempts to predict, based on independent variables (for example, different measures of the TACT) specific classes of a dependent variable (for example, all participants who received a certain score on the RAT). The dependent variable can be split into smaller and smaller classes (branches), till specific stopping rules are achieved (Galimberti and Soffritti, 2011 ; Brandmaier et al, 2013 ). Thus, this method strives to find clusters that represent a sufficient range of the dependent variable and are separable with an accepted error (Kopiez et al, 2006 ).…”

Section: Methodsmentioning

confidence: 99%

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Investigating the structure of semantic networks in low and high creative persons

Kenett

Anaki

Faust

2014

Front. Hum. Neurosci.

281

350

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According to Mednick's (1962) theory of individual differences in creativity, creative individuals appear to have a richer and more flexible associative network than less creative individuals. Thus, creative individuals are characterized by “flat” (broader associations) instead of “steep” (few, common associations) associational hierarchies. To study these differences, we implement a novel computational approach to the study of semantic networks, through the analysis of free associations. The core notion of our method is that concepts in the network are related to each other by their association correlations—overlap of similar associative responses (“association clouds”). We began by collecting a large sample of participants who underwent several creativity measurements and used a decision tree approach to divide the sample into low and high creative groups. Next, each group underwent a free association generation paradigm which allowed us to construct and analyze the semantic networks of both groups. Comparison of the semantic memory networks of persons with low creative ability and persons with high creative ability revealed differences between the two networks. The semantic memory network of persons with low creative ability seems to be more rigid, compared to the network of persons with high creative ability, in the sense that it is more spread out and breaks apart into more sub-parts. We discuss how our findings are in accord and extend Mednick's (1962) theory and the feasibility of using network science paradigms to investigate high level cognition.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Investigating the structure of semantic networks in low and high creative persons

Kenett

Anaki

Faust

2014

Front. Hum. Neurosci.

281

350

View full text Add to dashboard Cite

show abstract

“…This was achieved via a decision tree approach, which is a statistical method for analyzing multivariate data ( Lafond et al, 2009 ; Galimberti and Soffritti, 2011 ; Brandmaier et al, 2013 ). A decision tree attempts to predict based on independent variables (different measures of the TACT) specific classes of a dependent variable (all participants who received a certain score on the RAT).…”

Section: Methodsmentioning

confidence: 99%

“…A decision tree attempts to predict based on independent variables (different measures of the TACT) specific classes of a dependent variable (all participants who received a certain score on the RAT). The dependent variable can be split into smaller and smaller classes (branches), until specific stopping rules are achieved ( Galimberti and Soffritti, 2011 ; Brandmaier et al, 2013 ). Thus, this method strives to find clusters that represent a sufficient range of the dependent variable and are separable with an accepted error ( Kopiez et al, 2006 ).…”

Section: Methodsmentioning

confidence: 99%

“…This method derives decisions, or classification rules, which form the different branches of the tree. To classify the participants to the LSC and HSC groups, we applied the JMP software 1 classification and regression tree approach ( Galimberti and Soffritti, 2011 ), to predict performance in the RAT based on the different TACT fluency and quality scores. In this sense, this approach computes classification rules on how different ranges and combinations of the different TACT scores predict participants’ performance on the RAT.…”

Section: Methodsmentioning

confidence: 99%

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Metaphor Comprehension in Low and High Creative Individuals

2018

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The comprehension of metaphors involves the ability to activate a broader, more flexible set of semantic associations in order to integrate the meanings of the weakly related parts of the metaphor into a meaningful linguistic expression. Previous findings point to a relation between levels of creativity and efficiency in processing metaphoric expressions, as measured by reaction times (RTs) and error rates. Furthermore, recent studies have found that more creative individuals exhibit a relatively more flexible semantic memory structure compared to less creative individuals, which may facilitate their comprehension of novel metaphors. In the present study, lower and higher creative individuals performed a semantic relatedness judgment task on word pairs. These word pairs comprised four types of semantic relations: novel metaphors, conventional metaphors, literal word pairs, and meaningless word pairs. We hypothesized that the two groups will perform similarly in comprehending the literal, unrelated, and the conventional metaphoric word pairs. However, with respect to novel metaphors, we predicted that higher creative individuals will demonstrate better performance compared to lower creative individuals, as indicated by smaller RTs and more accurate responses. Our main finding shows that higher creative individuals were faster in comprehending both types of metaphors, conventional and novel, compared to lower creative individuals. Furthermore, higher creative individuals were significantly more accurate than lower creative individual only in comprehending novel metaphors. The findings are discussed in light of previous findings regarding the relation between metaphor comprehension, semantic memory, and creativity.

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Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis

Kenett

Salini

2011

Appl Stoch Models Bus & Ind

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Customer satisfaction is a key dimension driving business outcomes and performance of processes in service and product organizations. Measuring customer satisfaction is typically based on self-declared or interview-based questionnaires where users or consumers are asked to express opinions on statements, or satisfaction scales, mapping out various interactions with the service provider or product supplier. The topic has gained importance in recent years with researchers proposing new models and methods for designing, implementing, and analyzing customer satisfaction surveys. This paper builds on material presented in a recent edited book entitled Modern Analysis of Customer Satisfaction Surveys (Kenett and Salini, 2011). The book provides a comprehensive exposition of a variety of models that have all been applied to the same data set by leading experts. These models generate a variety of management insights. Combining models opens up opportunities for further research and applications. Specifically, we suggest that an integrated analysis, aggregating several approaches to survey data analysis, may prove effective in increasing the information quality derived from of a customer satisfaction survey.

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Tree‐Based Methods and Decision Trees

Cited by 5 publications

References 46 publications

Investigating the structure of semantic networks in low and high creative persons

Investigating the structure of semantic networks in low and high creative persons

Metaphor Comprehension in Low and High Creative Individuals

Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis

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