Instance-Based Learning

Mar 11, 2019

310 likes | 452 Views

Instance-Based Learning. Preview. K -nearest neighbor Other forms of IBL Collaborative filtering.

Share Presentation

Embed Code

Link

preview
collaborative filtering
nearest neighbor
instance based learning

guy-clements

Download Presentation

Instance-Based Learning

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Instance-Based Learning
Preview • K-nearest neighbor • Other forms of IBL • Collaborative filtering

Instance Based Learning

Instance Based Learning. IB1 and IBK Find in text Early approach. 1- Nearest Neighbor. Basic distance function between attribute-values If real, the absolute value If nominal, d(v1,v2) = 1 if v1 =v2, else 0.

331 views • 16 slides

Instance-Based Learning

Instance-Based Learning. By Dong Xu State Key Lab of CAD&CG, ZJU. Overview. Learning Phase Simply store the presented training examples. Query Phase Retrieve similar related instances. Construct local approximation. Report the function value at query point.

388 views • 27 slides

Instance Based Learning

Instance Based Learning . k -Nearest Neighbor Locally weighted regression Radial basis functions Case-based reasoning Lazy and eager learning. Instance-Based Learning. When to Consider Nearest Neighbor. Instance map to points in R n Less than 20 attributes per instance

799 views • 20 slides

Instance Based Learning

Instance Based Learning. Instance Based Learning. Classify based on local similarity Ranges from simple nearest neighbor to case-based and analogical reasoning Use local information near the current query instance to decide the classification of that instance

360 views • 21 slides

Instance Based Learning

Instance Based Learning. IB1 and IBK Small section in chapter 20. 1- Nearest Neighbor. Basic distance function between attribute-values If real, the absolute value If nominal, d(v1,v2) = 1 if v1 =v2, else 0. Distance between 2 instances is square root of sum of square.

267 views • 13 slides

Instance Based Learning

Instance Based Learning. Classify based on local similarity Ranges from simple nearest neighbor to case-based and analogical reasoning Use local information near the current query instance to decide the classification of that instance

392 views • 25 slides

Instance Based Learning

Instance Based Learning. Ata Kaban The University of Birmingham. Today we learn: K-Nearest Neighbours Case-based reasoning Lazy and eager learning. Instance-based learning. One way of solving tasks of approximating discrete or real valued target functions

462 views • 29 slides

Instance Based Learning

Instance Based Learning. Ata Kaban The University of Birmingham. Today we learn: K-Nearest Neighbours Locally weighted regression Case-based reasoning Lazy and eager learning. Instance-based learning. One way of solving tasks of approximating discrete or real valued target functions

600 views • 30 slides

Instance based and Bayesian learning

Instance based and Bayesian learning. Kurt Driessens with slide ideas from a.o . Hendrik Blockeel , Pedro Domingos , David Page, Tom Dietterich and Eamon Keogh. Overview. Nearest neighbor methods Similarity Problems: dimensionality of data, efficiency, etc. Solutions:

736 views • 62 slides

Chapter Eight Instance Based Learning

Chapter Eight Instance Based Learning. Machine Learning Tom M. Mitchell. Outline. Introduction K-Nearest Neighbor Locally Weighted Regression Radial Basis Functions Case-Based Reasoning Lazy and Eager Learning. What Is Instance Based Learning.

2.57k views • 33 slides

Instance Based Learning

Instance Based Learning. Introduction k-nearest neighbor Locally weighted regression Radial Basis Functions Case-Based Reasoning Summary. Introduction. Instance-based learning divides into two simple steps: 1. Store all examples in the training set.

353 views • 16 slides

Classification using instance-based learning

Classification using instance-based learning. Classification using instance-based learning. Introduction (lazy vs. eager learning) Notion of similarity (proximity, inverse of distance) k-Nearest Neighbor (K-NN) method Distance-weighted K-NN Axis stretching

389 views • 19 slides

Instance based learning

Instance based learning. 基于实例的学习. 上海交通大学. 摘自 T. Mitchell Machine learning. Topics. Introduction k-Nearest Neighbor Learning (kNN) Locally Weighted Regression(LWR) Radial Basis Function (RBF) IBL--NNet Case-Based Reasoning (CBR) Conclusion. IBL: Basic Idea. Key idea:

700 views • 48 slides

Instance-Based Learning

Instance-Based Learning. Content. Motivation Eager Learning Lazy Learning Instance-Based Learning k-Nearest Neighbour Learning (kNN) Distance-Weighted k-NN Locally Weighted Regression (LWR) Case-Based Reasoning (CBR) Summary. Motivation: Eager Learning.

576 views • 29 slides

4. Instance-Based Learning

4. Instance-Based Learning. 4.1 Introduction Instance-Based Learning: Local approximation to the target function that applies in the neighborhood of the query instance Cost of classifying new instances can be high: Nearly all computations take place at classification time

296 views • 18 slides

Instance-Based Learning

Instance-Based Learning. Evgueni Smirnov. Overview. Instance-Based Learning Comparison of Eager and Instance-Based Learning Instance Distances for Instance-Based Learning Nearest Neighbor (NN) Algorithm Advantages and Disadvantages of the NN algorithm

411 views • 25 slides

Instance Based Learning

Instance Based Learning. Nearest Neighbor. Remember all your data When someone asks a question Find the nearest old data point Return the answer associated with it In order to say what point is nearest, we have to define what we mean by "near".

336 views • 25 slides

Instance-Based Learning

Instance-Based Learning. Preview. K -nearest neighbor Other forms of IBL Collaborative filtering.

419 views • 30 slides

Instance-based Learning Algorithms

Instance-based Learning Algorithms. Presented by Yan T. Yang. Agenda. Background what is instance-based learning? Two simple algorithms Extensions [Aha, 1994]: F eedback algorithm Noise reduction Irrelevant attribute elimination Novel attribute adoption. Learning Paradigms.

465 views • 32 slides

Instance Based Learning

195 views • 16 slides

Instance Based Learning

167 views • 13 slides

Instance Based Learning

Instance Based Learning. Based on Raymond J. Mooney’s slides University of Texas at Austin. Example. Instance-Based Learning.

544 views • 52 slides

More Related