Term
What kind of algorithm is k-Mean clustering?
- Supervised learning
- Unsupervised learning
- Reinforcement learning
|
|
Definition
| k-Means is an unsupervised learning algorithm. |
|
|
Term
What are the two main goals that k-Means algorithm tries to accomplish? |
|
Definition
- It seeks to minimize the distance between points within a cluster.
- It seeks to maximize the distance between clusters.
|
|
|
Term
| Describe two common use cases for the k-Means algorithm. |
|
Definition
- Creating labeled groups that can used for a later classification.
- Anomaly detection.
|
|
|
Term
Describe the x main steps of the k-Mean algorithm. |
|
Definition
- Select k centroids (number of groups).
- Assign each sample to the closest centroid (group).
- Compute the mean of each group and assign those means as the new centroids for each group.
- Repeat until some stopping criteria is reached.
|
|
|
