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A fuzzy classification approach to piecewise regression models
Kang Ping Lu,
Shao Tung Chang
*
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Corresponding author for this work
Department of Mathematics
Research output
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Contribution to journal
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Article
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peer-review
9
Citations (Scopus)
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Dive into the research topics of 'A fuzzy classification approach to piecewise regression models'. Together they form a unique fingerprint.
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Mathematics
Piecewise
100%
Maximum Likelihood
100%
Differentiability
40%
Classes
40%
Detection
40%
Variance
40%
Modeling
20%
Real Data
20%
Transforms
20%
Parameters
20%
Regression Parameter
20%
Superiority
20%
Initial Value
20%
Likelihood Approach
20%
Data Structure
20%
Point Location
20%
Continuous Model
20%
Likelihood Function
20%
Earth and Planetary Sciences
Model
100%
Classification
100%
Regression
100%
Position (Location)
30%
Estimate
20%
Utilization
20%
Datum
20%
Area
20%
Parameter
20%
Detection
20%
Value
10%
Experiment
10%
Magnitude
10%
Coefficient
10%
Standard
10%
Calculation
10%
Effectiveness
10%
Data Set
10%
Mixture
10%
Transform
10%
Continuity
10%
Data Structure
10%
Computer Science
Models
100%
classification approach
100%
fuzzy classification
100%
Breakpoint
100%
maximum-likelihood
35%
Point Detection
14%
Application
7%
Standards
7%
Classes
7%
Experimental Result
7%
Data Structure
7%
Procedures
7%
Regression Parameter
7%
Initial Value
7%
Likelihood Function
7%
Fuzzy Clustering
7%
Data Application
7%
Class Variable
7%
Continuous Model
7%
INIS
fuzzy logic
100%
classification
100%
maximum-likelihood fit
62%
data
37%
applications
25%
detection
25%
comparative evaluations
12%
values
12%
modeling
12%
datasets
12%
mixtures
12%
smoothness
12%
Economics, Econometrics and Finance
Regression Model
100%
Location
60%
Measure of Dispersion
40%
Scientific Modelling
20%
Statistical Method
20%
Clustering
20%