python-scikit-learnK means clustering example
from sklearn import datasets, cluster
X, _ = datasets.load_iris(return_X_y=True)
model = cluster.KMeans(n_clusters = 3)
model.fit(X)
clusters = model.predict(X)ctrl + cfrom sklearn importimport module from scikit-learn | .KMeans(create KMeans clustering model |
n_clustersnumber of clusters we want to see | .fit(train model with a given features and target variable dataset |
.predict(predict target variable based on given features dataset | |
More of Python Scikit Learn
- Using OneClassSVM for outliers detection example
- Neural network example
- Grid search CV example
- Feature selection using KBest and chi2
- How to get best parameters from grid search CV
- How to inverse transform PCA reduced data
- How to get best estimator from grid search CV
- Use imputer for one column only
- Using quantile transformer example
- PCA dimensionality reduction example
See more codes...