DengAI

Reports and Presentations

Presentation for CS4622 (Machine Learning)

Report for CS4622 (Machine Learning)

Report for CS4642 (Data Mining and Information Retrieval)

Results

Current best result: 19.3798 (MAE), Rank 89 as of July 27 - 2018.
See Generated files for a complete list of intermediate generated files and submissions.

Directory contents

• The . root directory contains the data files downloaded from drivendata and some milestone submissions.
• deprecated folder contains the first approaches to the problem with Matlab regression learner and Orange3 (with minimal preprocessing) and the resulting .csv files.
• Neural Networks folder contains the first approaches to the problem with deep neural networks with Keras and Tensorflow.
• Negative Binominal Regression contains the DengAI benchmark model built with Jupyter Notebook and sklearn, statsmodels etc.
• Interactive Python 1 contains the approaches that do general preprocessing with Jupyter Notebook, pandas, sklearn, statsmodels, seaborn and uses various models for prediction.
• Interactive Python 2 contains a pipeline that processes the files in various stages using Jupyter Notebook, pandas, sklearn, statsmodels, seaborn, and R's STL (time series decomposition) borrowed with the r2py bridge. This pipeline does preprocessing, visualization, analysing, automatic selection of features, best model selection etc. The best working model is a time series decomposing predicter with a linear regression model.
• Orange folder contains an Orange3 pipeline that tests cross-validated errors of various learners with preprocessing, feature engineering etc.