Python for Machine Learning - The Complete Beginners Course - Defining the Classifier

Python for Machine Learning - The Complete Beginners Course - Defining the Classifier

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers the process of using the KMeans algorithm from sklearn to create a classifier with three clusters. It begins with importing the necessary library, setting up the classifier, and training the model using the fit method. The tutorial then demonstrates how to predict and store labels, and concludes by identifying the cluster centers. Future lectures will include plotting the clusters.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the first step in creating a K-Means classifier?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How do you specify the number of clusters in the K-Means algorithm?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What method is used to train the K-Means model?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

How do you obtain the cluster labels after fitting the model?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What do the cluster centers represent in K-Means clustering?

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