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kmeans_clustering

Summary of Steps:

  1. Import necessary libraries.
  2. Preprocess the data: Standardized the features to ensure equal contribution.
  3. Determine the optimal number of clusters using the Elbow method: The Elbow graph indicated 3 as the optimal number.
  4. Apply KMeans clustering: Clustered the data into 3 clusters.
  5. Visualize the clusters: Created a scatter plot to visually represent the clusters.

About

The dataset includes the following columns: Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, and Species. We will use the Sepal and Petal measurements to predict the optimum number of clusters using the KMeans algorithm.

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