To take this even one step further, you need to decide what percent of false negative vs. One of the options from this pop-up menu is Visualize Cluster Assignments. View communities Featured Developer Centers Jazz.net IBM Cloud Analytics DEV Bluemix API Explorer Featured destinations Swift IBM developerWorks Open Architecture center developerWorks Premium Career Concierge dW Open Architecture Center Swift IBM LearnOpen source ContentsIntroductionIntroductionClassification vs. United States English English IBM Site map IBM Learn Learn with our tutorials and training developerWorks provides tutorials, articles and other technical resources to help you grow your development skills on a wide variety of topics and products. There are 100 rows of data in this sample, and each column describes the steps that the customers reached in their BMW experience, with a column having a 1 (they made it to this step or looked at this car), or 0 (they didn't reach this step). They are hoping to mine this data by finding patterns in the data and by using clusters to determine if certain behaviors in their customers emerge.
BMW cluster algorithmView image at full sizeFinally, we want to adjust the attributes of our cluster algorithm by clicking SimpleKMeans (not the best UI design here, but go with it). Ultimately, they tend to buy M5s or Z4s (but never 3-series). Theoretically, there could be a tree with leaves = (rows * attributes). However, for the average user, clustering can be the most useful data mining method you can use. Cluster attributesView image at full sizeAt this point, we are ready to run the clustering algorithm. Ensure that Use training set is selected so we use the data set we just loaded to create our model. In this article, I will also make repeated references to the data mining method called "nearest neighbor," though I won't actually delve into the details until Part 3. Other important numbers are in the "ROC Area" column, in the first row (the 0.616); I'll explain this number later, but keep it in mind.
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