10 lines (8 loc) · 1018 Bytes

MachineLearning

iPython Notebooks - implementing some machine learning algorithms

1. Analysis of Housing Data - Regression Models¶

Asia Mitchell - May 1st, 2016

I have used the Boston Housing dataset from the CMU StatLib Library and built regression models to predict the median value of housing in thousands. This dataset contains 13 attribute values (1 binary attribute, and the remaining are continuous).

2. Linear Discriminant Analysis for Renal Tumor Grade Classifer

Asia Mitchell - June 2016

There is very limited information regarding the clinical and molecular features of high and low Fuhrman grade ccRCCs. Using clinical and DNA mutation data, I built a linear classifier for Fuhrman grade in ccRCCs. I used leave-one-out cross-validation to determine how well the LDA model generalizes.