Iris_Classification

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Iris_Classification

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Iris classification with Python Scikit-learn :blossom:

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# Iris Classification with Python Scikit-learn :blossom:

## Medium Post
Check out my Medium post "Exploring Classifiers with Python Scikit-learn — Iris Dataset" [here](https://medium.com/@terryz_/exploring-classifiers-with-python-scikit-learn-iris-dataset-2bcb490d2e1b?source=friends_link&sk=a4111634175b4daf06fed3873da5fd48).

## Table of Content
  * [Demo](#demo)
  * [Overview](#overview)
  * [Motivation](#motivation)
  * [Procedures](#procedures)
  * [Models](#models)
  * [Installation](#installation)
  
## Demo
Check out a simple web demo I created and deployed with Heroku here: https://dehao-iris-clf.herokuapp.com/. This web app displays model prediction results based on user-input parameters.

## Overview
This is a simple classification task performed on the Iris dataset - one of the best known dataset in the world of data science.

## Motivation
I am definitely not a flower expert, but with the help of a dataset with 150 iris instances with their petal/sepal measurements, can I be one? Also which of the petal/sepal measurements are more useful features to look at?

## Procedures
  * Import Libraries and Load Dataset
  * Numerical Summary
  * Train-Test Split
  * Exploratory Data Analysis
  * Model Development
  * Further Discussion

## Models
  * Classification Tree
  * Gaussian Naive Bayes Classifier
  * Linear Discriminant Analysis
  * Quadratic Discriminant Analysis
  * K Nearest Neighbors
  * Logistic Regression
  * Support Vector Machine (linear kernel and polynomial kernel)
  
## Installation
```bash
pip install -r requirements.txt
```

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