Ayantika22 / Flask_Iris_Dataset-program

This Flask program is used to display the Prediction of Iris Species.

Flask_Iris_Dataset

This Flask program is used to display the Prediction of Iris Species.

Iris dataset are taken into consider to form a wed-based Flask App.

Install Anaconda(Open Source Package)

Either use Spyder or Ipython .

I have used Spyder Notebook to run this Flask App.

Create a virtual environment before running Flask app.

Install Numpy, Flask, Pandas using Pip command.

First Run the model.py

Then app.py

Path for running the app User/ User_Name/ Anaconda3/ Folder name/ Paste Flask Iris from github

Unzip

Open Spyder console . Then flask-Seed folder

After running app.py Copy the 127.0.0.1:5000/ using mouse button

Don't press ctrl+ C from keyboard else the console will exit the running part

Paste the url in browser and Enter the dataset value in order to predict Iris Species.

For more information, Cite this paper if referred.

1. http://www.ijitee.org/wp-content/uploads/papers/v9i7/G5943059720.pdf

2. https://www.researchgate.net/profile/Ayantika_Nath2/publication/341671505_Clustering_Visualization_and_Class_Prediction_using_Flask_of_Benchmark_Dataset_for_Unsupervised_Techniques_in_ML/links/5ece482292851c9c5e5f8695/Clustering-Visualization-and-Class-Prediction-using-Flask-of-Benchmark-Dataset-for-Unsupervised-Techniques-in-ML.pdf

3. https://www.researchgate.net/profile/Ayantika_Nath2/publication/341150281_Clustering_Using_Dimensional_Reduction_Techniques_for_Energy_Efficiency_in_WSNs_A_Review/links/5eb10592299bf18b9595b113/Clustering-Using-Dimensional-Reduction-Techniques-for-Energy-Efficiency-in-WSNs-A-Review.pdf

Citing the paper(if referred) is mandatory since the paper has copyrights.

Enjoy Coding