About this repository

This repository is a Flask App that has a machine learning model merged with it and deployed on heroku.
This predicts famous iris species among Versicolor, Setosa and Virginica

Here is picture of thosed species

ML model used

In this repository I have used Linear Support Vector Classsification model pre-built in sklearn for predicting classes. LinearSVC works well for datasets having less data and less atrributes to train the model. Dataset used has only 150 data samples overall so LinearSVC performed well with accuracy of 93% and predicted only 3 test data wrong.

Predicted classes visualization

Scatter plot between attributes and categorized using color based on predictions

Petal width VS Petal length

Petal width VS Petal length

More visualization can be found in jupyter notebook in this repository itself named: Flowers Identification using svm.ipynb

Libraries used

• Numpy
• Pandas
• Seaborn
• Matplotlib
• Sklearn