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General health orientation based psychological motivations for masters athletes, a consideration of clustering utilizing t-distributed Stochastic Neighbor Embedding
 

General health orientation based psychological motivations for masters athletes, a consideration of clustering utilizing t-distributed Stochastic Neighbor Embedding

Joe Walsh, Ian Timothy Heazlewood, Mark DeBeliso Mike Climstein
The Sport Journal, Vol.21
2020

(1)

url
https://thesportjournal.org/article/general-health-orientation-based-psychological-motivations-for-masters-athletes-a-consideration-of-clustering-utilizing-t-distributed-stochastic-neighbor-embedding/
Published (Version of record)

t-SNE Sport psychology Motivations of Marathoners Scales (MOMS) scikit-learn library LimeSurvey Exercise Physiology Other Health
An exploration of clustering of general health orientation psychological motivations for participation in sport was conducted using t-distributed Stochastic Neighbor Embedding (t-SNE). The aim of this research was to assess the suitability of applying t-SNE to creating two-dimensional scatter plots to visualise the relationship between different general health orientation motivators. The data source used for this investigation was survey data gathered on World Masters Games competitors using the Motivations of Marathoners Scales (MOMS). Application of t-SNE plots could assist in visually mapping general health orientation psychological constructs and gaining greater understanding of the underlying patterns in the MOMS tool. Some clustering patterns were observed, with some items in the MOMS connected in a logical manner that complied with those originally proposed by the developers of the MOMS. On tuning the t-SNE model hyperparameters, it became apparent that the t-SNE graphs were able to provide an appropriate representation of clustering with learning rates outside the ranges often recommended (at the time of writing). As t-SNE is a relatively modern approach to visualizing high dimensional data, this was a finding worth reporting. Two-dimensional scatter plots produced using t-SNE may assist in creating hypotheses about the relationships present between psychological constructs in such high-dimensional data.
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