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Aprenda Perform K-means Clustering | Basic Clustering Algorithms
Cluster Analysis

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Perform K-means Clustering

Tarefa

Swipe to start coding

Let's check the efficiency of the algorithm on different types of clusters. Now we will use the three built-in datasets of the sklearn library and try to use the K-means algorithm to cluster the corresponding points. We will provide visualizations and try to estimate the quality of clustering using these visualizations.

Your task is to use the K-means clustering algorithm and to solve 3 different clustering problems. Compare the results and make conclusions about clustering quality. You have to:

  1. Use KMeans class from cluster module for import.
  2. Use KMeans class to instantiate a class object
  3. Use.fit()method to train model.
  4. Use .labels_attribute to extract fitted clusters.

Once you've completed this task, click the button below the code to check your solution.

Solução

Note

In visualizations, it is necessary to look not at the color of clusters, but at the relative position of points in real and predicted clusters (Python can color the same clusters with different colors in different pictures due to implementation features)

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Seção 2. Capítulo 2

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book
Perform K-means Clustering

Tarefa

Swipe to start coding

Let's check the efficiency of the algorithm on different types of clusters. Now we will use the three built-in datasets of the sklearn library and try to use the K-means algorithm to cluster the corresponding points. We will provide visualizations and try to estimate the quality of clustering using these visualizations.

Your task is to use the K-means clustering algorithm and to solve 3 different clustering problems. Compare the results and make conclusions about clustering quality. You have to:

  1. Use KMeans class from cluster module for import.
  2. Use KMeans class to instantiate a class object
  3. Use.fit()method to train model.
  4. Use .labels_attribute to extract fitted clusters.

Once you've completed this task, click the button below the code to check your solution.

Solução

Note

In visualizations, it is necessary to look not at the color of clusters, but at the relative position of points in real and predicted clusters (Python can color the same clusters with different colors in different pictures due to implementation features)

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 2. Capítulo 2
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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