You Implemented K Means Clustering To Group Patients Records In Hospital Into 3 Clusters Using The Following Features 1 (16.96 KiB) Viewed 25 times
You Implemented K Means Clustering To Group Patients Records In Hospital Into 3 Clusters Using The Following Features 2 (61.07 KiB) Viewed 25 times
You implemented K-means clustering to group patients' records in hospital into 3 clusters using the following features: sex, height, weight, age and income. After plotting a pair-wise plot of the clusters, you noticed that there is significant overlap between the clusters. What should you do? O Remove one of the features Decrease the number of clusters Identify additional features to add to the analysis Increase the number of clusters
Given the below decision tree, Color 1 Blue 1 Width Red 1 NO Green 1 Height Tall Thin! 1 NO Fati 1 YES Short| 1 NO YES the new example (A) would be classified as NO Class Example A Color Red Height Short Width Thin O True O False
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