Module 3 Project

By David Cuervo

Background

Build a classifier to accurately predict the condition of water wells in Tanzania.

Folder containing the original data sets from DrivenData
CSV of cleaned data
Data_Cleaning Notebook: contains the code for exploring and cleaning the original data set
Modeling Notebook: contains code for building the best classifier
PNG image of Tanzania and the wells plotted
PDF of project presentation
Rubric for Module 3 Project

Began by downloading the data from DrivenData
Worked through data set column by column to deal with missing data, outliers, and catigorical variables
Exported cleaned data and used it so begin building classifiers
Used Boruta as feature selection
Used the features selected through Boruta to build logistic regression, decision tree, and random forest models

Construction year, waterpoint type, and GPS height were the most important features in the model

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
Data_Cleaning (1).ipynb		Data_Cleaning (1).ipynb
Modeling (1).ipynb		Modeling (1).ipynb
README.md		README.md
Tanzania_Water_Well_plot_map.png		Tanzania_Water_Well_plot_map.png
Tanzanian Water Well Data (1) (1).pdf		Tanzanian Water Well Data (1) (1).pdf
cleaned_well_data2.csv		cleaned_well_data2.csv
module_3_project_rubric.pdf		module_3_project_rubric.pdf
test_set_values.csv		test_set_values.csv
training_set_values.csv		training_set_values.csv
well_status.csv		well_status.csv