Conteúdo do Curso

Clustering Demystified

Introduction Import Necessary Libraries and Data Preliminary Analysis Data Preparation Declare Feature Vector and Target Variable Convert Categorical Variable into Integers Feature Scaling K-Means Model with 2 Clusters Check the Quality How many Clusters?K-Means Model with 4 Clusters

Check the Quality

Now that we have trained our clustering algorithm we have to evaluate its performances to assess the results.

Methods description

.labels_: This attribute of the KMeans object contains the cluster labels assigned to each data point after fitting the KMeans algorithm to the data;
y == labels: This is a comparison operation that checks element-wise equality between two arrays y and labels, resulting in a boolean array;
correct_labels: This variable stores the count of data points that were correctly labeled, i.e., assigned to the correct cluster.

Tarefa

Compare the correct_labels with the predicted ones.
Print the results.

Mark tasks as Completed

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Seção 1. Capítulo 9

AVAILABLE TO ULTIMATE ONLY

Methods description

.labels_: This attribute of the KMeans object contains the cluster labels assigned to each data point after fitting the KMeans algorithm to the data;

y == labels: This is a comparison operation that checks element-wise equality between two arrays y and labels, resulting in a boolean array;

correct_labels: This variable stores the count of data points that were correctly labeled, i.e., assigned to the correct cluster.