lime-explainer

There are 2 repositories under lime-explainer topic.

prrao87 / fine-grained-sentiment-app
A Flask LIME explainer app for fine-grained sentiment classification.
flask web-app lime-explainer lime nlp interpretability visualization
Language:Python 11
prrao87 / fine-grained-sentiment-app-streamlit
A LIME explainer app for fine-grained sentiment classification, written using Streamlit.
streamlit explainer nlp interpretability web-app visualization lime lime-explainer
Language:Python 3
prrao87 / fine-grained-sentiment-app-dash
A LIME explainer app for fine-grained sentiment classification, written using Dash.
dash explainer nlp interpretability visualization lime lime-explainer web-app
Language:Python
shilpakancharla / metoo-classification
Social media provides a unique opportunity to shed light on phenomena that have previously been ignored or swept under the rug. The #MeToo movement began in 2006 when Tarana Burke first coined the phrase, but a viral Twitter post in 2017 served to lift the hashtag into the mainstream accompanied by the public reckoning of several high-profile men. This hashtag allows people to seek solidarity on a much larger scale in calling out the perpetrators of their abuse. We are going to categorize tweets with #MeToo into the years they were posted. In particular, we look at the years 2017, 2018, and 2019.
metoo-tweets metoo-movement datasets hashtag kaggle lime convolutional-neural-networks fasttext lstm-neural-networks classification social-media lime-explainer
Language:Jupyter Notebook

prrao87 / fine-grained-sentiment-app