Iris Flower Classification

One of the very famous classification problems in Machine Learning is the IRIS Flower classification problem. This Blog Post aims at understanding this problem and the underlying concepts of machine learning

Problem Statement:

Given Sepal and Petal lengths and width predict the class of Iris

Dataset Link : https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

Data Description :

Attribute Information:
   1. sepal length in cm
   2. sepal width in cm
   3. petal length in cm
   4. petal width in cm
   5. class: 
      -- Iris Setosa
      -- Iris Versicolour
      -- Iris Virginica

Basic Data Analysis :

1. The dataset provided has 150 rows
2. Dependent Variables : Sepal length.Sepal Width,Petal length,Petal Width
3. Independent/Target Variable : Class
4. Missing values : None

Code : data.info()
Output :

<class ‘pandas.core.frame.DataFrame’>
RangeIndex: 150 entries, 0 to 149
Data columns (total 5 columns):
sepal_length 150 non-null float64
sepal_width 150 non-null float64
petal_length 150 non-null float64
petal_width 150 non-null float64
class 150…