Disaster-Response-Classifier

Getting Started

The Disaster Response Classifier project hosts a Flask web application which aids an emergency worker to classify disaster messages into several categories.

Prerequisites

The following libraries are used for the project:

    pandas
    SQLAlchemy
    nltk
    scikit-learn
    plotly
    flask

Extract Transform Load Pipeline

To execute the ETL pipeline, go to the folder data and follow the below command.

python process_data.py disaster_messages.csv disaster_categories.csv DisasterResponse.db

Machine learning Pipeline

To execute the Machine learning pipeline, go to the folder models and follow the below command.

python train_classifier.py ../data/DisasterResponse.db classifier.pkl

Running the Server

Go to the folder app and run the file run.py

python run.py

Classification Report

The classification report for the multiclass classifier can be obtained by running the machine learning pipeline.