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Cluster Analysis
course content

Course Content

Cluster Analysis

Cluster Analysis

1. What is Clustering?
Formulation Of The ProblemWhat Is Unique About Clustering?Types Of Clustering
2. Basic Clustering Algorithms
K-means Clustering Perform K-means ClusteringAgglomerative ClusteringPerform Agglomerative ClusteringMean Shift Clustering DBSCAN ClusteringPerform DBSCAN ClusteringUsing Clustering On Real Data
3. How to choose the best model?
Internal EvaluationExternal EvaluationQuality Evaluation

bookPerform Agglomerative Clustering

Task
test

Swipe to show code editor

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).

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Section 2. Chapter 4
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bookPerform Agglomerative Clustering

Task
test

Swipe to show code editor

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).

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 4
toggle bottom row

bookPerform Agglomerative Clustering

Task
test

Swipe to show code editor

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).

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Task
test

Swipe to show code editor

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).

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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