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AI-900 · Question #185

AI-900 Question #185: Real Exam Question with Answer & Explanation

The correct answer is A: Split the original dataset into a dataset for training and a dataset for testing.. Understand steps for clustering You can think of the steps to train and evaluate a clustering machine learning model as: 1. Prepare data: Identify the features and label in a dataset. Pre-process, or clean and transform, the data as needed. 2. Train model: Split the data into two

Submitted by javi_es· Mar 30, 2026

Question

You need to create a clustering model and evaluate the model by using Azure Machine Learning designer. What should you do?

Options

  • ASplit the original dataset into a dataset for training and a dataset for testing.
  • BUse the original dataset for training and evaluation.
  • CSplit the original dataset into a dataset for features and a dataset for labels.
  • DSplit the original dataset into a dataset for training and a dataset for testing.

Explanation

Understand steps for clustering You can think of the steps to train and evaluate a clustering machine learning model as: 1. Prepare data: Identify the features and label in a dataset. Pre-process, or clean and transform, the data as needed. 2. Train model: Split the data into two groups, a training and a validation set. Train a machine learning model using the training data set. Test the machine learning model for performance using the validation data set. 3. Evaluate performance. 4. Deploy a predictive service: After you train a machine learning model, you need to convert the training pipeline into a real-time inference pipeline. Then you can deploy the model as an application on a server or device so that others can use it. clustering-model

Topics

#Clustering models#Model evaluation#Azure Machine Learning designer

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