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项目作者： thefirebanks

项目描述 ：
Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting
高级语言： Python
项目地址: git://github.com/thefirebanks/Ensemble-Learning-for-Tweet-Classification-of-Hate-Speech-and-Offensive-Language.git


Ensemble Learning for Tweet Classification of Hate Speech and Offensive Language - Winter/Spring Project 2018

These programs are part of a project that will use an ensemble learning model to detect offensive language and hate speech in tweets. It is composed of:

  • A Voting classifier
  • An LSTM network
  • A Bayesian model
  • A Proximity model

Link to full project: https://github.com/quinnbp/WT2018

This repository contains:

Voting classifier for hate-speech and offensive language detection in tweets:

  • Uses a hard-voting (majority voting) classifier that evaluates the outputs of:

    • An SGD Classifier with log loss
    • A LinearSVM Classifier with L1 feature selection and L2 classification
    • A Perceptron

  • Features:

    • TFIDF matrix
    • POS-Tags matrix
    • Sentiment analysis
    • Prescence-of-lexicon-terms score
    • Word embeddings (random and GloVe)

TODO:

  • Try improving word embeddings using a neural network based on [2]

Weighting system for ensemble learning

  • Has 3 different options for applying weighted voting:
    • Precision score of the classifiers’ confusion matrices
    • CEN score
    • Precision + CEN score
    • Equal voting

Confusion matrix class

  • Creates a confusion matrix given the output predictions of a classifer and the set of true labels
  • Contains operations like getting precision score, storing it as a pdf, getting number of false positives, getting the CEN score of the matrix, etc.

All written by Daniel Firebanks

Inspired by the research of: