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Claire Zhang

Recently Published

Source Predictions with Text Analysis
My partners and I predicted the source based on a word from the articles we chose. We chose articles about sleep from Scientific American and Time Magazine and split each article into paragraphs to increase the size of our data set. Then we tokenized our words and used factors such as the amount of times a word showed up in a particular source to predict which source a given word would come from. We used both supervised and unsupervised learning (Hierarchical Clustering, PCA) to do this.
Predicting Good Wines and Bad Wines
In this assignment, we (my partners and I) used k-Nearest Neighbors, Linear Discriminant Analysis, and Decision Trees to predict which wines in a new data set would be classified as good quality wines and which ones would be classified as bad quality wines.
k-Nearest Neighbors: GPA and Years to Graduate
Predicting years to graduate from a person's GPA
Test 1
Abortion and Crime/Income