rasbt--python-machine-learning-book
wehub-resource-sync
17 行
612 B
Markdown
17 行
612 B
Markdown
Sebastian Raschka, 2015
|
|
|
|
Python Machine Learning - Code Examples
|
|
|
|
## Chapter 11 - Working with Unlabeled Data – Clustering Analysis
|
|
|
|
- Grouping objects by similarity using k-means
|
|
- K-means++
|
|
- Hard versus soft clustering
|
|
- Using the elbow method to find the optimal number of clusters
|
|
- Quantifying the quality of clustering via silhouette plots
|
|
- Organizing clusters as a hierarchical tree
|
|
- Performing hierarchical clustering on a distance matrix
|
|
- Attaching dendrograms to a heat map
|
|
- Applying agglomerative clustering via scikit-learn
|
|
- Locating regions of high density via DBSCAN
|
|
- Summary |