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Applying Supervised Machine Learning (XGBoost) to predict visitor to customer conversion for an online store

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Predicting-Customer-Conversion-through-Supervised-Machine-Learning

Applying Supervised Machine Learning (XGBoost) to predict visitor to customer conversion for an online store

In this project, I have applied XGBoost, a well-known Supervised Learning Algorithm to predict the probability of a visitor to an online store making a purchase (i.e. generating revenue).

The following files are available in this directory:

  1. Code_File.py: This is the Python file that contains the code that I developed for this project

  2. Dataset Description.pdf: This is a pdf document in which I have described the attributes of the dataset.

  3. Results of Exploratory Data Analysis.pdf: This file contains the discussion of the results of EDA.

  4. input_training_data.csv: This file contains the training data in csv form

  5. input_training_data.csv: This file contains the test data in csv form

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Applying Supervised Machine Learning (XGBoost) to predict visitor to customer conversion for an online store

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