Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Perform Agglomerative Clustering | Basic Clustering Algorithms
Cluster Analysis
course content

Contenido del Curso

Cluster Analysis

Cluster Analysis

1. What is Clustering?
2. Basic Clustering Algorithms
3. How to choose the best model?

Perform Agglomerative Clustering

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 2. Capítulo 4
toggle bottom row

Perform Agglomerative Clustering

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 2. Capítulo 4
toggle bottom row

Perform Agglomerative Clustering

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Tarea

Your task is to use different linkage types and to look at the performance of agglomerative clustering on moons and circles datasets. You have to:

  1. Import AgglomerativeClustering class from sklearn.cluster module.
  2. Add a parameter with the name linkage as an input of the function.
  3. Add .fit() method of the agglomerative object to train the model.
  4. Use 'single', 'complete', and 'average' as parameters of the function(parameters in the code have to be used in the same order).

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 2. Capítulo 4
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
We're sorry to hear that something went wrong. What happened?
some-alt