Machine Leaning

Bamberg University

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Summary

PPT of Instance Based Learning
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29

January 2022

2004/2005
One way of solving tasks of approximating discrete or real valued target functions
riyadhalgburi
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Summary

Classification: k Nearest Neighbours
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3

January 2022

2005/2006
Recall that in classification problems, the task is to decide to which of a predefined, finite set of categories an object belongs. In this lecture, we look at another classification method. The method we look at is known as the k-nearest-neighbours or kNN method
riyadhalgburi
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Summary

Instance Based Learning
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16

January 2022

2004/2005
k-Nearest Neighbor Locally weighted regression Radial basis functions Case-based reasoning Lazy and eager learning
riyadhalgburi
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Summary

INTRODUCTION TO MACHINE LEARNING
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188

January 2022

2004/2005
Learning, like intelligence, covers such a broad range of processes that it is difficult to define precisely. As regards machines, we might say, very broadly, that a machine learns whenever it changes its structure, program, or data (based on its inputs or in response to external information) in such a manner that its expected future performance improves. Some of these changes, such as the addition of a record to a data base, fall comfortably within the province of other disciplines and are not...
riyadhalgburi
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Summary

k-Nearest Neighbour
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65

January 2022

2007/2008
● Organisational Matters ● k-Nearest Neighbour Distance is the Essential Ingredient Inductive Bias Extensions of k-Nearest Neighbour ● Probability Theory ● Naive Bayes Problem Estimating Probabilities Solution: Independence Assumption
riyadhalgburi
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