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partial_results
.gitignore
README.md
dataExtractor.py
dataset.csv
fast_test_script.py
getFeatures.py
inferred_text.npy
regression.py
script.py
textLearning.py

README.md


1- Run the project

1-Download a doc2vec model (https://github.com/jhlau/doc2vec) and unpack it in the folder 2-run the file script.py 3-follow the instructions to select the target, the features and the cardinality of the training set 4-The predictions will be saved in the partial results folder

Run fast_test_script.py if you prefer to skip the interactive part, but you have to modify the code in order to select the features.

NOTE: you need to manually comment the PCA and feature selection functions in dataExtractor.py if you don't want to use them.


2- Dataset

The dataset needs to be in the .csv format. It is composed as follows: 1- User Stories (String) 2- Business Value (String) 3- User Story Elaboration (String) 4- Definition of done (String) 5- Expected output (String) 6- LOC (int) 7- New classes (int) 8- Changed classes (int) 9- Effort (int) 10- N. Unit Test (int) 11- Entropy (int) 12- Services (Matrix of int)