KNOWLEDGE DISCOVERY DATA

Rosalía Iñiguez
Mind Map by Rosalía Iñiguez, updated more than 1 year ago
Rosalía Iñiguez
Created by Rosalía Iñiguez over 6 years ago
12
0

Description

Principales aspectos de la obtención del conocimiento con Knowledge Discovery Data

Resource summary

KNOWLEDGE DISCOVERY DATA
  1. ITERATIVE SEQUENCE OF STEPS
    1. DATA CLEANING
      1. DATA INTEGRATION
        1. DATA SELECTION
          1. DATA TRANSFORMATION
            1. DATA MINING

              Annotations:

              • PROCESS OF DISCOVERING INTERESTING PATTERN AND KNOWLEDGE FROM LARGE AMOUNTS OF DATA
              1. DESCRIPTIVES
                1. PREDICTIVES
                  1. DOMAINS
                    1. STATISTICS

                      Annotations:

                      •  Statistics studies the collection, analysis, interpretation or explanation, and presentation of data  
                      1. MACHINE LEARNING

                        Annotations:

                        •  Machinelearning investigates how computers can learn (or improve their performance) based on data  
                        1. PATTERN RECOGNITION
                          1. DATABASE
                            1. DATA WAREHOUSE
                              1. INFORMATION RETRIEVAL
                                1. VISUALIZATION
                                  1. ALGORITHMS
                                    1. HIGH PERFORMANCE COMPUTING
                                    2. PATTERNS CAN BE MINED DATA MINING FUNCTIONALITIES
                                      1. DISCRIMINATION

                                        Annotations:

                                        • DISCRIMINATION: COMPARISON OF FEATURES OF ONE CLASS DATA OBJETC AGAINST GENERAL FEATURES OF OBJECTS FROM ONE OR MULTIPLE CLASS OBJECTS CHARACTERIZATION:  summarizing the data of the class under study (often called the target class) in general terms  
                                        1. FREQUEN PATTERNS

                                          Annotations:

                                          •  There are many kinds of frequent patterns, including frequent itemsets, frequent subsequences (also known as sequential patterns), and frequent substructures.  
                                          1. SUPPORT
                                            1. CONFIDENCE
                                              1. accuracy and coverage
                                              2. ASSOCIATIONS
                                                1. CORRELATIONS
                                                  1. CLASSIFICATION AND REGRESSION

                                                    Annotations:

                                                    •  Classification is the process of finding a model (or function) that describes and distinguishes data classes or concepts.  Regression analysis is astatistical methodology that is most often used for numeric prediction,   
                                                    1. CLUSTERING ANALYSIS AND OULIER ANALYSIS

                                                      Annotations:

                                                      •  Unlike classification and regression, which analyze class-labeled (training) data sets, clustering analyzes data objects without consulting class labels.  
                                                      1. INTERESTING PATTERNS
                                                        1. NOVEL
                                                          1. CERTAINTY
                                                            1. POTENTIALLY USEFUL
                                                              1. EASILY UNSDERSTOOD
                                                                1. PATTERN INTERSTINGNESS
                                                                  1. SUBJECTIVE
                                                                    1. OBJECTIVE
                                                                2. DATA CAN BE MINED
                                                                  1. DATABASES
                                                                    1. DATA WAREHOUSES
                                                                      1. TRANSACTIONAL DATA
                                                                        1. MANY OTHERS
                                                                        2. ISSUES OF DATA MINING RESEARCH
                                                                          1. MINING METHODOLOGIES
                                                                            1. USER INTERACTION
                                                                              1. EFFICIENCY AND SCALABILITY
                                                                                1. DIVERSITY OF DATA TYPES
                                                                                  1. DATA MINING AND SOCIETY
                                                                                  2. VIEWS
                                                                                    1. APPLICATION
                                                                                      1. TECHNOLOGIES
                                                                                        1. DATA
                                                                                          1. KNOWLEDGE
                                                                                        2. PATTERN EVALUATION

                                                                                          Annotations:

                                                                                          • ¿Interesante?:  (1) easily understood byhumans, (2) valid on new or test data with some degree of certainty, (3) potentiallyuseful, and(4) novel. A pattern is also interesting if it validates a hypothesis that the user sought to confirm.  
                                                                                          1. KNOWLEDGE PRESENTATION
                                                                                          2. APPLICATIONS
                                                                                            1. BUSINESS INTELIGENCE
                                                                                              1. WEB SEARCH
                                                                                                1. BIOINFORMATICS
                                                                                                  1. HEALTH INFORMATICS
                                                                                                    1. FINANCE
                                                                                                      1. DIGITAL LIBRARIES
                                                                                                        1. DIGITAL GOVERMENT
                                                                                                        Show full summary Hide full summary

                                                                                                        Similar

                                                                                                        “In knowledge there is always a trade-off between accuracy and simplicity.” Evaluate this statement
                                                                                                        sanchopu
                                                                                                        English test
                                                                                                        Víctor Alvarado
                                                                                                        English environments
                                                                                                        Lady Rios
                                                                                                        GOOD TEACHER
                                                                                                        Pilar Villagaray
                                                                                                        Information Security in Big Data: Privacy and Data Mining
                                                                                                        Francisco Flores
                                                                                                        Data mining
                                                                                                        Omar Jacobo
                                                                                                        Big Data-DL
                                                                                                        Diego Lopez
                                                                                                        DIAGNOSTIC TEST
                                                                                                        Wilmar Cifuentes
                                                                                                        The role of knowledge management in innovation
                                                                                                        Carlos Vicente Moreno Roballo
                                                                                                        MINERÍA DE DATOS
                                                                                                        Gusttavo Nipas
                                                                                                        Future continuous
                                                                                                        lozanoyair8