This is our collaborative project for the kaggle titanic contest.

gendermodel.py : legacy file illustrating the basics predict.py : legacy file manually constructing survival tables and data analysis randforest.py : legacy file with a first pass at random forests (without sibsp and parch)

Help_Explore_Explain.py : various help stuff

PrepareTitanicData.py : regularizes and floats the data. call function titandata() to get data, test8, or testdata UPDATE: can now call original data in string format with "originaldata" argument. convertages() function now in this file.

predictions.py: contains several functions that create survival predictions on a given data set, compares predictions to each other, and tests them on the training data. These will be called by higherlevel.py and/or other files. UPDATE: The function randomforests() will run many random forests and yield the average prediction for each passenger.

higherlevel.py: A main file for doing analysis work and playing with the data. Numerous cuts through the data are shown, to try to gain insight. Random forests are implemented. Several predictions are compared to each other.

DataFilters.py: The functions df() and dfrange() are particularly powerful for filtering the data. showstats() presents the results for a data set in a nice format.

BayesianAnalysis.py:

linearregression1.py:

MultivariateRegression.py: