TAILIEUCHUNG - Chapter 3: Nearest neighbor based classifiers

Chapter 3: Nearest neighbor based classifiers is Introduction; Nearest Neighbor algorithm, Variants of the NN algorithm, Data Reduction, Prototype reduction, Z-score normalization, Modified k-Nearest Neighbor algorithm and somethings else. | Chapter 3 Nearest neighbor based classifiers Assoc. Prof. Dr. Duong Tuan Anh Faculty of Computer Science and Engineering, HCMC Univ. of Technology 3/2015 Outline Introduction Nearest Neighbor algorithm Variants of the NN algorithm Data Reduction Prototype reduction 1. Introduction One of the simplest decision procedures that can be used for classification: the nearest neighbor algorithm. The nearest neighbor based classifiers use some or all patterns in the training set to classify a test pattern. These classifiers involve finding the similarity between the test pattern and every pattern in the training set. Lazy learners: do less work when a training pattern is presented and more work when making a classification. NN classifier lazy learner, instance-based learner 2. Nearest Neighbor algorithm The nearest neighbor (NN) algorithm assign to a test pattern the class label of its closest neighbor. Let there be n training patterns, (X1,c1), (X2, c2), ,(Xn, cn), where Xi is of .

• Cơ sở dữ liệu
• Nearest neighbor based classifiers
• Nearest Neighbor algorithm
• Variants of the NN algorithm
• Data Reduction
• Prototype reduction
• Z score normalization
• BMC Bioinformatics
• High throughput screening
• K nearest neighbor
• Linear discriminant analysis
• Classification methods