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The Mining and Analysis of Data with Mixed Attribute Types
Ed Wakelam
, Neil Davey
,
Yi Sun
, Amanda Jefferies
, Parimala Alva
, Alex Hocking
Centre for AI and Robotics Research
Biocomputation Research Group
Department of Computer Science
School of Physics, Engineering & Computer Science
Hertfordshire Business School
Research output
:
Chapter in Book/Report/Conference proceeding
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Conference contribution
355
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Dive into the research topics of 'The Mining and Analysis of Data with Mixed Attribute Types'. Together they form a unique fingerprint.
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Keyphrases
Numeric Data
100%
Mixed Attributes
100%
Nominal Data
100%
Student Data
100%
Systematic Comparison
33%
Trainer
33%
Student Achievement
33%
Learning Path
33%
Adaptive Learning System
33%
Education Business
33%
Teaching Efficiency
33%
Business Studies
33%
Life Challenges
33%
Data Analytics
33%
Artificial Intelligence
33%
Learning Materials
33%
Major Contributor
33%
Business Intelligence
33%
Novel Technique
33%
Education Field
33%
Computer Science
Influence Student
100%
Nominal Data Analysis
100%
Large Data Set
100%
Adaptive Learning
100%
Data Analytics
100%
Artificial Intelligence
100%
Learning System
100%
Business Intelligence
100%
Data Analysis
100%
Social Sciences
Student Success
100%
Analysis of Large Data Set
100%
Economic Education
100%
Artificial Intelligence
100%
Data Analytics
100%
Engineering
Nominal Data
100%
Learning System
50%
Real Life
50%
Artificial Intelligence
50%
Success Rate
50%
Economics, Econometrics and Finance
Qualitative Method
100%
Analysis of Large Data Set
50%
Data Analytics
50%
Economic Education
50%