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2061741
Data pre-processing
Description
Mind Map on Data pre-processing, created by Saravanakumar on 18/02/2015.
Mind Map by
Saravanakumar
, updated more than 1 year ago
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Created by
Saravanakumar
about 9 years ago
27
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Resource summary
Data pre-processing
Data cleaning
Missing values
Ignore the tuple
Fill in the missing value manually
Use a global constant to fill in the missing value
Use the attribute mean to fill in the missing value
Use the attribute mean for all samples belonging to the same class as the given tuple
Use the most probable value to fill in the missing value
Use the most probable value to fill in the missing value
Noisy data
Annotations:
Noise is a random error or variance in a measured variable.
Binning
Regression
Clustering
Data cleaning as a process
Data integration and transformation
Data Integration
Data Transformation
Smoothing
Aggregation
Generalization
Normalization
Attribute construction
Data reduction
Data cube aggregation
Attributes subset selection
Stepwise forward selection
Stepwise backward elimination:
Combination of forward selection and backward elimination
Decision tree induction
Dimensionality reduction
Numerosity reduction
Data discretization and concept hierarchy generation
Why Preprocess the Data?
Data Discretization and Concept Hierarchy Generation
Discretization and Concept Hierarchy Generation for Numerical Data
Concept Hierarchy Generation for Categorical Data
Descriptive Data Summarization
Measuring the Central Tendency
Measuring the Dispersion of Data
Graphic Displays of Basic Descriptive Data Summaries
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