UARK (University of Arkansas )
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Predicting True Attributes of Retailer Data
No full textIn the rapidly evolving landscape of consumer-packaged goods (CPG) retail, understanding the true values of various factors influencing sales performance is paramount for strategic decision-making and effective resource allocation. In ensuring accuracy of data points, the CatBoost model is utilized, a state-of-the-art gradient boosting technique, to predict the true attribution values of datasets sourced from CPG industry retailers.
By leveraging CatBoost’s inherent capabilities to handle categorical data and its robustness against overfitting, the models are optimized to accurately predict the true attribution values for various items. The performance of the CatBoost models is evaluated through rigorous cross-validation techniques and compared against baseline models to assess their effectiveness in predicting attribution values. The results demonstrate the efficacy of the CatBoost algorithm in accurately predicting true attribution values, thereby providing valuable insights for CPG retailers to optimize their marketing strategies, promotional activities, and pricing tactics. Overall implications of this research extend to enhancing decision-making processes and improving understanding of items within the database.
This project was worked on and completed during an internship with Nuqleous, a retail intelligence software company. Over the course of a year, this project was refined and improved upon so that Nuqleous customers could determine if any of their data attributes were false, and if so, get the predicted value for that instance
Using Empathy to Shift Climate Change Attitudes.
Get PDFIt has shifted from a hunch to an existential threat, it is a harbinger of disaster and bankruptcy, backed by science, and yet a considerable portion of Americans still believe that climate change is a hoax. It is becoming increasingly imperative to convince this portion to join the fight. It has been found that empathy is an effective method of persuasion, prompting the question of whether empathy could be used shift climate change attitudes. The hypothesis of this study was that if a person feels empathy for somebody harmed by the effects of climate change, they will be more willing than someone who hasn’t to perform behavior that mitigates the effects of climate change. Student participants (n = 100) were recruited from a social psychology class to listen to a prepared radio broadcast. Half were told to remain stoic while listening to the broadcast, focusing on the technical aspects and sound quality. The other half were asked to pay attention to how the subject of the story might feel. Participants were then asked questions on how they would vote on issues related to climate change as well as which actions they would be willing to take to help mitigate its effects. Analysis of the results found no significant effect of the manipulation of empathy on climate change attitudes. However, a strong correlation (r=.36) was found between feeling empathetic and willingness to take action to mitigate climate change
