-
Notifications
You must be signed in to change notification settings - Fork 337
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
f11fcec
commit 9492876
Showing
7 changed files
with
52,743 additions
and
0 deletions.
There are no files selected for viewing
Binary file not shown.
Binary file not shown.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,20 @@ | ||
# Fetal Health Classification | ||
|
||
## Overview | ||
The goal is to analyze tweets to classify them into categories of cyberbullying and non-cyberbullying using NLP techniques and machine learning models. | ||
|
||
## Dataset | ||
The dataset contains over 47,000 tweets labeled into six categories: Age, Ethnicity, Gender, Religion, Other type of cyberbullying, and Not cyberbullying. | ||
|
||
Link to the dataset: [Fetal Health Classification Dataset](https://www.kaggle.com/datasets/andrewmvd/cyberbullying-classification/data) | ||
|
||
|
||
## Models Used | ||
|
||
1. Logistic Regression | ||
2. Naive Bayes | ||
3. Random Forest Classifier | ||
4. Voting Classifier (Ensemble Model): Combines predictions from the above models using a majority voting scheme. | ||
|
||
## Contribution | ||
Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to improve the system. |
Binary file not shown.
Binary file not shown.
Oops, something went wrong.