Browsing by Author "Karan, Baris"

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    Dog Walker Segmentation
    (IEEE, 2022) Ercan, Alperen; Karan, Baris; Çakar, Tuna
    In this study dog walkers were separated into clusters according to walkers' walk habits. Due to the fact that the distributions were non-normal, normalization algorithms were applied before the onset of clustering. After normalizing, K Means algorithm and Gaussian Mixture Models used for finding optimum cluster count. According to these clusters, walkers' consecutive months separated to follow-up their behavioral traits. This part of the study adds value to the project to examine walkers' behaviors closer.
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    Predicting Animal Behaviours: Physical and Behavioural Classification Of Dog Walking Levels
    (IEEE, 2022) Ozen, Guris; Karan, Baris; Çakar, Tuna
    Methods of predicting canine behaviour is an area covered by canine behaviour experts. This study aims to predict the behaviour of dogs during walking based on available information about dogs. In this data-driven project based on up-to-date company data, the problem of predicting dog behaviour was addressed in two different ways. First, it is aimed to create a supervised classification model. Within the scope of this study, improvements were made to various classification algorithms. The results were analyzed in different axes. Secondly, it is aimed to create a new parameter that predicts dog walking difficulties by formulating the parameters.