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- All Subjects: bag-of-words
- All Subjects: Counseling
- Creators: Jimenez Arista, Laura
- Creators: Barolli, Adeiron
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
Indian-American young adults are often caught between the cultures of their parents and their environment, and these two cultures can impact their views based on the cultures' views. In this project, I created an overview of personal accounts of Indian-American young adults on their experiences with mental health struggles, and receiving counseling and treatment. This study analyzed a sample of accounts and testimonials previously collected through a qualitative review. I found that many of the Indian-American young adults were open to mental health counseling and treatment, but saw Indian cultural views as a barrier.