Kaggle-Automated-Essay-Checking-System

My attempt for the Kaggle AES project (https://www.kaggle.com/c/asap-aes) The linear regression model uses a Word2Vec model and custom generated heuristic features to obtain a mean-quadratic-weighted-kappa score of 0.9359.

Notebooks:

1. CustomFeatureGeneration.ipynb - Generating custom features for the data set.
2. Data_Exploration.ipynb - Exploring the data set and free form visualization.
3. Linear Regression Model.ipynb - The model building and learning takes place here.

Helper functions and required library import:

./utils/helperfunctions.py
./utils/requirements.py

Libraries used for the Capstone Project:

1. Scikit-learn 0.18.1: pip install --user --upgrade sklearn
2. Gensim 2.1.0: pip install --user --upgrade gensim
3. Textmining 1.0: pip install --user --upgrade textmining
4. Grammar Check 1.3.1 : 1. pip install --upgrade 3to2 2. pip install --user --upgrade grammar-check
5. Matplotlib 2.0.0: pip install --user --upgrade matplotlib
6. NLTK 3.2.2: pip install --user --upgrade nltk

NOTE You need to download all the NLTK's data first inorder to use its packages, to do so type following commands in python (referece: http://www.nltk.org/data.html)

• import nltk
• nltk.download()
• You also need Java installed on your machine to run NLTK. Java installation steps for Ubuntu 16.04 : (http://www.wikihow.com/Install-Oracle-Java-on-Ubuntu-Linux)

7.** Dataset : domain123.csv **

• ** Images and saved models : ./model_and_visualization/**
• ** References : ./References/ **
  <<<<<<< HEAD
• ** Essay set description : ./Essay_Set_Descriptions ** =======
• ** Essay set description : ./Essay_Set_Descriptions **

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