Analyzing Test Data Using K means Clustering:

In this article, we discuss about an example of K means clustering on sample random data by using open-cv library in python for data science.

We will visualize test data with multiple features using matplot-lib tool.

Analyzing Test Data Using K means Clustering in Python for Data Science

OUTPUT:

Analyzing Test Data Using K means Clustering in Python for Data Science

Now we will apply k means clustering algorithm to the above illustration and see how it behaves.

We should follow the below mentioned steps:

  1. First, we will set a test data.
  2. Then we will define the criteria and apply k means().
  3. Then we will separate the data.
  4. In the final stage, we will plot the data.

Analyzing Test Data Using K means Clustering in Python for Data Science

OUTPUT:

Analyzing Test Data Using K means Clustering in Python for Data Science

Applications:

  1. While identification of cancerous data.
  2. While the prediction of a student’s academic performance.
  3. The prediction of drug activity.

So, to learn more about it in python for data science, you can check this and this as well.

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