You are using an Azure Machine Learning designer pipeline to train and test a K-Means clustering model. You want your model to assign items to one of three clusters. Which configuration property of the K-Means Clustering module should you set to accomplish this? Set Number of Centroids to 3Set Random number seed to 3Set Iterations to 3

.Find the k-means class in the sklearn documentation and import it. Train the model for three user clusters with the random_state parameter set to 12345. Print the centroid values of the resulting clusters on the screen.

Item #1: (Demos Demonstration)Demonstrate in Demos the standard algorithm implementation for K-means clustering for k=3 and using the dataset from below. Post screenshotsDataset:(-3,7), (-4,6),(-5,5.5),(-5.45,5.8),(-1,3),(-1,2),(1,1),(2,2),(2.1,2.7),(5,5),(6,5.5)

In K-Means clustering, the number of clusters, k, must be specified in advance.

2.Find out how you can pass the initial centroids to the model in the documentation of the k-means class. Add the code that will launch model training with initial centroids (defined by the centers variable) to the precode. Print the cluster centroids for the model from the previous task (in precode), as well as the cluster centroids for a model with initial centroids.

You use Azure Machine Learning designer to create a training pipeline for a clustering model. Now you want to use the model in an inference pipeline. Which module should you use to infer cluster predictions from the model? Score ModelAssign Data to ClustersTrain Clustering Model