quboanthony / human-or-robot

Kaggle facebook recruit iv- classification of human or robot bidders on the bidding website.

facebook-recruiting-iv-human-or-bot

• Udacity capstone project
• by: Bo QU

In python 3

• data_investigation.ipynb Jupyter notebook file with codes of Data Exploration.
• human-or-robot.ipynb Jupyter notebook file for the main codes for solving the project.

Packages:

• pandas
• numpy
• math
• scikit-learn
• dmlc xgboost
• seaborn
• matplotlib
• scipy

Data set

Data set from kaggle project website: https://www.kaggle.com/c/facebook-recruiting-iv-human-or-bot/data

References links:

[1] Garbage in, garbage out: https://en.wikipedia.org/wiki/Garbage_in,_garbage_out

[2] Receiver operating characteristic: https://en.wikipedia.org/wiki/Receiver_operating_characteristic

[3] Kaggle project website: https://www.kaggle.com/c/facebook-recruiting-iv-human-or-bot

[4] Population stability index: https://www.listendata.com/2015/05/population-stability-index.html

[5] Numpy log: https://docs.scipy.org/doc/numpy/reference/generated/numpy.log.html

[6] MinMaxScaler: http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html

[7] XGBoost: https://xgboost.readthedocs.io/en/latest/#

[8] Gradient Boosting: https://machinelearningmastery.com/gentle-introduction-gradient-boosting-algorithm-machine-learning/

[9] Random Forest: https://en.wikipedia.org/wiki/Random_forest

[10] Adaboost: https://en.wikipedia.org/wiki/AdaBoost

[11] Extra-Trees: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.65.7485&rep=rep1&type=pdf

[12] Scikit-learn: http://scikit-learn.org/stable/index.html

[13] dmlc XGboost: https://github.com/dmlc/xgboost

[14] Seaborn: http://seaborn.pydata.org/

[15] Matplotlb: https://matplotlib.org/

[16] Population stability index: http://ucanalytics.com/blogs/population-stability-index-psi-banking-case-study/

[17] Guide to parameter tuning in XGBoost: https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/

[18] Kaggle ensembling guide: https://mlwave.com/kaggle-ensembling-guide/