Mobility is one of the potential factors in contributing to the spread of COVID-19. Our goal is to estimate the effect of state-wide policies on mobility signals at a county-level.
The goal of this project is to construct a model for a given sentence and the label sentiment to predict what phrases in the sentence that best support the given sentiment.
We explore the potential of creating new recipes via text data. Our goal has two folds. First, we aim to classify the cuisine based on ingredients. Second, we want to predict an ingredient that is missing from a given list of ingredients and a cuisine name.
In this work, we would like to explore the characteristics of this bike share system and try to come up with recommendations to provide potential solutions for the questions above based on data analysis wtih the Citi Bike system 2019 data that is publicly available.
It classifies fraudulent credit card transactions based on the result of a PCA transformation. We explore various classic classification algorithms in this work.
We aim to resolve the traditionally tedious and time consuming task of determining the age of abalone by constructing predictive models of the ages of abalones using other physical measures that are easier to obtain.
We aim to train a classifier to accurately classify a person whether or not has a heart disease problem. The dataset is provided by UCI Machine Learning Repository.
This work provides insights on how to design a neural network to work with spam filtering problem.
We estimated probabilities for tetrahedral and triangular dice using the sphere projection method and multivariate calculus. To test our results, we printed several dice of varying sizes. After a few thousand initial rolls, we realized that our calculations weren’t accurately describing the situation and that bias could have been introduced due to rolling the dice by hand. Therefore, we built a machine to roll the dice.
This project predicts the patient inflow at Pali Momi Hospital's Emergency Room (ER) and provides recommendations for how to optimize scheduling for their ER's doctors and mid-level providers.