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Machine Learning Assignment: Minimal Distance Classifier and Condensed Set, Exercises of Computer Science

Dhirubhai Ambani Institute of Information and Communication Technology Computer Science

A machine learning assignment focusing on the minimal distance classifier (mdc) and the concept of condensed sets. The assignment includes instructions for using the mdc to classify a test pattern, finding the condensed set for a three-class dataset, and observing the impact of data processing order on the condensed set. Additionally, it covers using cluster centroids as prototypes for pattern classification.

Typology: Exercises

2012/2013

Uploaded on 03/28/2013

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Download Machine Learning Assignment: Minimal Distance Classifier and Condensed Set and more Exercises Computer Science in PDF only on Docsity! Assignment 1. Let the training set consist of patterns in the following table. Let the test patten be P = (3.0, 2.0)t. Use the Minimal Distance Classifier (MDC) to classify P using the training data shown in Table. 2. Consider the three-class data set shown in the following table. Let the patterns be considered in the order X1 to X12. What is the resulting Condensed set? 3. Consider a two-class problem with the following training dataset. Class1 : 1 : (1, 2), 2 : (2, 2), 3 : (2, 1) Class2 : 4 : (2.7, 2), 5 : (4, 2), 6 : (4, 1). Obtain the Condensed set if we process the data in the order 1, 2, 3, 4, 5, and 6. What happens if we consider the data in the order 2, 3, 1, 4, 5, and 6? 4. Use the MNNC to obtain Condensed using the data given in problem 5. Use each class as a cluster in the data given problem 1. Use the cluster centroids as prototypes and classify pattern P = (3, 2)t. Docsity.com

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