I am using built-in dataset iris from sklearn for clustering. In KMeans I set the number of clusters in advance but it is not true for DBSCAN. How to train a model if you dont set the number of clusters in advance?

I tried:

```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#%matplotib inline

from sklearn.cluster import DBSCAN,MeanShift
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split,KFold,cross_val_score
from sklearn.metrics import accuracy_score,confusion_matrix

iris = load_iris()
X = iris.data
y = iris.target

dbscan = DBSCAN(eps=0.3,min_samples=10)

dbscan.fit(X,y)

```

I have got stuck on it!