Data Mining for Co-location Patterns
portes grátis
Data Mining for Co-location Patterns
Principles and Applications
Zhou, Guoqing
Taylor & Francis Ltd
01/2022
210
Dura
Inglês
9780367654269
15 a 20 dias
508
Descrição não disponível.
Chapter 1 Introduction
Chapter 2 Fundamentals of Mining Co-Location Patterns
Chapter 3 Principle of Mining Co-Location Patterns
Chapter 4 Manifold Learning Co-Location Pattern Mining
Chapter 5 Maximal Instance Co-Location Pattern Mining Algorithms
Chapter 6 Negative Co-Location Pattern Mining Algorithms
Chapter 7 Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation
Chapter 8 Application of Mining Co-Location Patterns in Buffer Analysis
Chapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery Classification
Index
Chapter 2 Fundamentals of Mining Co-Location Patterns
Chapter 3 Principle of Mining Co-Location Patterns
Chapter 4 Manifold Learning Co-Location Pattern Mining
Chapter 5 Maximal Instance Co-Location Pattern Mining Algorithms
Chapter 6 Negative Co-Location Pattern Mining Algorithms
Chapter 7 Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation
Chapter 8 Application of Mining Co-Location Patterns in Buffer Analysis
Chapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery Classification
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Co-location Patterns;3D Modeling;Data Set;Urban Feature Extraction;Spatial Feature Type;Urban Orthophotomap, Urban Image Classification;Participation Index;Big Data, Machine Learning;Maximal Clique;Land Use and Land Cover;Decision Tree Induction;Urban Planning;Join Operation;Co-location Algorithms;Decision Tree;Leaf Node;Data Sets;Mining Spatial Data;Table Instances;Spatial Data Set;Neighbor Relationship;Minimum Frequency Threshold;Spatial Data;Nonspatial Data;Maximal Instances;Buffer Algorithm;Univariate Decision Trees;Generalized Buffer;Polygon Buffer;Point Buffer
Chapter 1 Introduction
Chapter 2 Fundamentals of Mining Co-Location Patterns
Chapter 3 Principle of Mining Co-Location Patterns
Chapter 4 Manifold Learning Co-Location Pattern Mining
Chapter 5 Maximal Instance Co-Location Pattern Mining Algorithms
Chapter 6 Negative Co-Location Pattern Mining Algorithms
Chapter 7 Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation
Chapter 8 Application of Mining Co-Location Patterns in Buffer Analysis
Chapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery Classification
Index
Chapter 2 Fundamentals of Mining Co-Location Patterns
Chapter 3 Principle of Mining Co-Location Patterns
Chapter 4 Manifold Learning Co-Location Pattern Mining
Chapter 5 Maximal Instance Co-Location Pattern Mining Algorithms
Chapter 6 Negative Co-Location Pattern Mining Algorithms
Chapter 7 Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation
Chapter 8 Application of Mining Co-Location Patterns in Buffer Analysis
Chapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery Classification
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Co-location Patterns;3D Modeling;Data Set;Urban Feature Extraction;Spatial Feature Type;Urban Orthophotomap, Urban Image Classification;Participation Index;Big Data, Machine Learning;Maximal Clique;Land Use and Land Cover;Decision Tree Induction;Urban Planning;Join Operation;Co-location Algorithms;Decision Tree;Leaf Node;Data Sets;Mining Spatial Data;Table Instances;Spatial Data Set;Neighbor Relationship;Minimum Frequency Threshold;Spatial Data;Nonspatial Data;Maximal Instances;Buffer Algorithm;Univariate Decision Trees;Generalized Buffer;Polygon Buffer;Point Buffer
