Columbus Web Analytics Wednesday September 2019
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Dr. Michael Levin's presentation on Cluster Analysis presented September 18th, 2019 at Columbus Web Analytics Wednesday
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Columbus Web Analytics Wednesday September 2019
- 1. Sorting Customers into Groups Web Analytics Wednesday Michael Levin mlevin@otterbein.edu @MichaelALevin
- 3. Differing Forms of Machine Learning Supervised Unsupervised Categorial Data Classification Association Analysis Continuous Data Regression Clustering & Dimension Reduction
- 7. Types of Clustering Hierarchical K-Means
- 8. Step 0: Select Variables Revenue ($) Number of Downloads (#) Frequency of Purchase (#) Activities Registered (#) Number of Items in Basket (#) Percent of Emails Clicked (%) Cost of Acquisition ($) Number of Pages (#) Time Since Last Purchase
- 9. Step 1: Specify Number of Clusters
- 10. Step 2: Radom Assignment
- 11. Step 3: Compute Initial Centroids
- 12. Step 4: Re-Assign Each Point
- 13. Step 5: Re-Compute Centroids
- 14. 3 Cluster Solution Cluster % Black % Hispanic % Asian Median Age Unemp. Rate Per Capita Income 1 12 27 3 30 8 19 2 29 3 2 32 7 21 3 10 5 29 36 5 28 Distance 207.64
- 15. 4 Cluster Solution Cluster % Black % Hispanic % Asian Median Age Unemp. Rate Per Capita Income 1 14 28 6 30 9 21 2 15 4 2 32 5 20 3 48 3 1 32 9 22 4 10 5 29 36 5 30 Distance 165.35
- 16. 5 Cluster Solution Cluster % Black % Hispanic % Asian Median Age Unemp. Rate Per Capita Income 1 14 28 6 30 9 21 2 15 4 2 32 5 20 3 48 3 1 32 9 22 4 11 9 21 36 6 30 5 1 5 71 37 5 24 Distance 145.75
- 17. Decide on Number Cluster 3 Clusters 4 Clusters 5 Clusters Dallas 1 1 1 Austin 1 2 2 Atlanta 2 3 3 Boston 2 2 2 Seattle 3 4 4 Honolulu 3 4 5
- 18. Add to Supervised Learning Cluster Cluster 1 Cluster 2 Cluster 3 Cluster 4 Dallas 1 0 0 0 Austin 0 1 0 0 Atlanta 0 0 1 0 Boston 0 1 0 0 Seattle 0 0 0 1 Honolulu 0 0 0 1
- 19. Sorting Customers into Groups Web Analytics Wednesday Michael Levin mlevin@otterbein.edu @MichaelALevin
Editor's Notes
- Title slide with playing cards
- How can you sort these cards? Color. Number non-number. Suit. High value. Low value. Blackjack Runs by number Runs by order Whole deck of card Each card Sorting the cards gets us to cluster. Similar/Dissimilar. Parsimony. Actionable
- Supervised – we need a teacher or analysis to make decisions about the model. Train the data. Regression – predict value of a house or price willing to pay Classification – is this email spam or not I am simplifying here. Unsupervised – algorithm makes the decision Association – people who buy X also buy Y. Basket analysis Clustering – grouping items, observations, people based on variables. Other forms besides clustering such as preference or perceptual maps and factor analysis
- Photos Row of different mobile devices Row of different tablets Row of different laptops
- Photos Laptop and Mobile devices (2) 4 laptops & 4 mobile (8) 8 laptops, 8 mobile, 8 tablets
- Photos Email Responsive webdesign Offers
- Four types of clustering. Most stats oriented packages include hierarchical and non hierarchical. Hierarchical – do not know how many groups. K-Means – need to specify number of groups to start. Performs better with large datasets
- Select the number of variables. Consider what is important to your customer profile.
- Specify the desired number of clusters K : Let us choose k=2 for these 5 data points in 2-D space.
- Randomly assign each data point to a cluster : Let’s assign three points in cluster 1 shown using green color and two points in cluster 2 shown using grey color.
- Compute cluster centroids : The centroid of data points in the green cluster is shown using green cross and those in grey cluster using grey cross.
- Re-assign each point to the closest cluster centroid : Note that only the data point at the bottom is assigned to the red cluster even though its closer to the centroid of grey cluster. Thus, we assign that data point into grey cluster
- Re-compute cluster centroids : Now, re-computing the centroids for both the clusters.
- Photos Parsimony
- Photos Parsimony
- Photos Parsimony
- As I add more clusters, I am getting more homogenous groups.
- When I have decided on a solution, I can link the cluster results to regression or other supervised learning by converting the cluster results to dummy results.
- Title slide with playing cards