no code implementations • 28 May 2018 • Chaehan So
To this aim, the present work explores a well-documented neural style transfer algorithm (Johnson 2016) in four experiments on four relevant visual parameters: number of iterations, learning rate, total variation, content vs. style weight.
no code implementations • 29 Feb 2020 • Chaehan So
This paper analyzes how candidate choice prediction improves by different psychological predictors.
no code implementations • 29 Feb 2020 • Chaehan So
The current work analyzed these online reviews by sentiment analysis and used the extracted sentiments as features to predict the product ratings by several machine learning algorithms.
no code implementations • 29 Feb 2020 • Chaehan So
This paper investigates how accurately the prediction of being an introvert vs. extrovert can be made with less than ten predictors.
no code implementations • 29 Feb 2020 • Chaehan So
Hence, this work proposes a new process framework, Human-in-the-learning-loop (HILL) Design Cycles - a design process that integrates the structural elements of agile and design thinking process, and controls the training of a machine learning model by the human in the loop.
no code implementations • 3 Mar 2020 • Chaehan So
The present work aimed to gain an understanding of a machine learning model's prediction mechanism by visualizing the effect of sentiments extracted from online hotel reviews with explainable AI (XAI) methodology.
BIG-bench Machine Learning Explainable Artificial Intelligence (XAI) +1