This project is only for NUS machine learning course assignment, which creates one model to predict house price.

Environment Setup

(1) Installation List

a. python 3.6.2 (exe)<br />

b. PyQt5 (pip install pyqt5)<br />

c. scikit-learn (pip install scikit)<br />

d. python IDE(PyCharm community - exe)<br/>

(2) File List
[1] feature_ranking.py - rank data set features.
[2] ml.ui - Qt interface file.
[3] ml_ui.py - generated py file using .ui file. do not modify this file.
[4] ml_engine.py - all code about machine learning algorithm will be included in this file.
[5] ml__main.py - it is program entry and will interact with Qt UI.
[6] org_kc_house_data.csv - orginal data set.
[7] pre_kc_house_data.csv - preprocessing data set.
[8] plot_data.py - all code about data plotting will be here.
[9] preprocess_data.py - process orginal data set, and then write it into pre_kc_house_data.csv.