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iris-dataset iris k-means-clustering k-means-implementation-in-python k-means pca principal-component-analysis numpy pandas labelencoder clustering jupyter-notebook

iris-k_means-pca's Introduction

IRIS-K_Means-PCA

We will implementing PCA and k-means clustering on the iris dataset. The corresponding Python code is available in iris_PCA_KMeans.ipynb.

Each row in the dataset corresponds to an iris flower

There are 4 independent variables – sepal length, sepal width, petal length and petal width. There is 1 target variable ‘Species’ with 3 possible labels - ‘Iris-setosa’, ‘Irisversicolor’ and ‘Iris-virginica’

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