twitter_hate_speech 源码

qqseemingly85768 5 0 ZIP 2021-04-17 19:04:07

twitter_hate_speech 已实施的端到端自然语言处理项目将目标仇恨言论与仅包含令人讨厌的单词的言论区分开来。从数据清理,特征提取(单词包,nGrams,TF-IDF BOW,word2vec嵌入),特征选择和建模。使用word2vec CBOW和Skip-gram进行无监督学习。还创建了用于转移学习的多层感知器和用于半监督学习的标签传播算法。

文件列表

twitter_hate_speech-master.zip (预估有个78文件)

twitter_hate_speech-master

.gitignore 50B

deliverables

Milestone_3.pdf 1.02MB

feature_selection_colin_-_Jupyter_Notebook.pdf 1.49MB

feature_selection_colin_-_Jupyter_Notebook-merged.pdf 1.71MB

Week2_Features_Sean - Jupyter Notebook.pdf 1024KB

Week3 ML Implementation - Logistic regression + full dataset_Sean - Jupyter Notebook.pdf 908KB

Hate_Speech_-_Milestone_Four.pptx 613KB

Hate_Speech_-_Milestone_Two.pptx 1.77MB

Milestone_3-merged.pdf 1.34MB

Feature Engineering on Text Data - SZ.pdf 574KB

Week2_Features_Sean - with supervised learning W2v.pdf 1.49MB

Hate_Speech_-_Milestone_Two.pdf 2.07MB

Feature Engineering Text Data - Traditional Strategies_SZ.pdf 590KB

Week1_Problem,Dataset, Exploratory Data Analysis-checkpoint - Jupyter Notebook.pdf 985KB

Hate_Speech_-_Milestone_One.pptx 809KB

data

.ipynb_checkpoints

Automated Hate Speech Detection and the Problem of Offensive Language Python 3.6-checkpoint.ipynb 39KB

labeled_data.csv 2.43MB

Automated Hate Speech Detection and the Problem of Offensive Language Python 3.6.ipynb 53KB

labeled_data.p 3.18MB

Automated Hate Speech Detection and the Problem of Offensive Language.ipynb 82KB

readme.md 642B

semi_supervised_learning.ipynb 38KB

.DS_Store 6KB

sample learning curve.png 27KB

transfer_learning

tfidf_df.csv 48.64MB

.ipynb_checkpoints

Independent_Transfer_Learning_SZ-checkpoint.ipynb 36KB

labeled_data.csv 2.43MB

Independent_Transfer_Learning_SZ.ipynb 34KB

trained_embedding.csv 6.03MB

df_clean.csv 1MB

twitter_feature_array.csv 5.09MB

notebooks

Final_Week_Feature_Selection_Colin.ipynb 295KB

tfidf_df.csv 48.64MB

.ipynb_checkpoints

Week3 Training curve (separate for memory reasons)-checkpoint.ipynb 8KB

Create BOW-checkpoint.ipynb 72B

Week3 ML Implementation - Logistic regression + full dataset_Sean-checkpoint.ipynb 456KB

Untitled-checkpoint.ipynb 72B

Week1_Problem,Dataset, Exploratory Data Analysis-checkpoint-checkpoint.ipynb 85KB

Week3 Training curve - Random Forest-checkpoint.ipynb 152KB

Final Feature selection _ Sean-checkpoint.ipynb 72B

Full dataset cleaned and TFIDF-checkpoint.ipynb 912KB

feature_selection_colin-checkpoint.ipynb 1.99MB

Final_Week_Feature_Selection_Colin-checkpoint-checkpoint.ipynb 217KB

Week2_Features_Sean-checkpoint.ipynb 278KB

Random Forest Full Dataset-checkpoint.ipynb 242KB

RF and LR on Balanced Set-checkpoint.ipynb 863KB

Final Modeling-checkpoint.ipynb 516KB

Week3 Stacking-checkpoint.ipynb 5KB

Week2_Feature Selection-checkpoint-checkpoint.ipynb 72B

Univariate Data Exploration-checkpoint.ipynb 82KB

RF and LR on Balanced Set.ipynb 863KB

labeled_data.csv 2.43MB

Week3 ML Implementation - Logistic regression + full dataset_Sean.ipynb 456KB

Week2_Feature Selection-checkpoint.ipynb 74KB

feature.csv 5.49MB

Create BOW.ipynb 18KB

Full dataset cleaned and TFIDF.ipynb 34KB

Final Feature selection _ Sean.ipynb 46KB

Untitled.ipynb 72B

univariate_dataset.csv 10.07MB

Week3 Training curve (separate for memory reasons).ipynb 201KB

trained_embedding.csv 6.03MB

Week3 Training curve - Random Forest.ipynb 151KB

Week2_Features_Sean.ipynb 329KB

Week3 Stacking.ipynb 36KB

twitter_hate.db 8.33MB

feature_selection_colin.ipynb 3.51MB

Week1_Problem,Dataset, Exploratory Data Analysis-checkpoint.ipynb 912KB

Univariate Data Exploration.ipynb 82KB

df_clean.csv 969KB

Final_Week_Feature_Selection_Colin-checkpoint.ipynb 295KB

twitter_feature_array.csv 5.09MB

Final Modeling.ipynb 516KB

seanz.db 0B

Random Forest Full Dataset.ipynb 191KB

README.md 473B

individual_project_transfer_learning.ipynb 168KB

decisionregions.png 38KB

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twitter_hate_speech 源码

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