dm:start:clustering
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Guidelines for the homework on clustering
- Data Understanding: useful as a preliminary step to capture some data property that can help the clustering analysis (8 points)
- Distribution data analysis and suitable transformation of variables
- Elimination of redundant variables by correlation analysis
- Clustering Analysis by K-means: (15 points)
- Identification of the best value of k
- Characterization of the obtained clusters by using both analysis of the k centroids and comparison of the distribution of variables within the clusters and in the whole dataset
- Analysis by density-based clustering (7 points)
- Study of the clustering parameters
- Characterization and interpretation of the obtained clusters
- Analysis by hierarchical clustering (Optional - 3 points)
- Analysis to be performed on a sampling of the data for scalability reasons
dm/start/clustering.1355839756.txt.gz · Ultima modifica: 18/12/2012 alle 14:09 (12 anni fa) (modifica esterna)