Dense Spatial clustering of applications with noise ( DBCSAN ) — this is a clustering algorithm that was proposed in 1996. In 2014, the algorithm was awarded the "Test of Time" award at the leading Data Mining conference, KDD.
Dataset — Credit Card .
Step 1: Import Required Libraries
Step 2: Load data
Step 3: Data preprocessing
Step 4: Downsizing the data to make it renderable
Step 5: Building the clustering model
# Numpy array of all cluster labels assigned each data point
DBSCAN ( eps
). fit (X_principal)
Step 6: Visualize clustering
Step 7: Setting Model Parameters
Step 8: Visualize the changes