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Independent Components Analysis (ICA)
Acceptability For Sale
Agency Testing
Alcoholic Beverages
Analysis
Animated Sequences
Anova-Simultaneous Component Analysis (ASCA)
Aroma
Artificial Intelligence
B-Cluster Analysis
BSG-Enriched Biscuits
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Beer
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Brettanomyces Metabolites
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Confidence Ellipsoid
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Consumer
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Consumer Satisfaction
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Correspondence Analysis
Cross-Modal Interactions
Crossdiff-Unfolding
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Dairy
Data Analysis
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Degree-Of-Difference
Descriptive Analysis
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Discriminability
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Drivers and Inhibitors of Liking
Dual-Attribute Time Intensity (DATI)
Effect Size
Emotions
Equivalence
Exports
FCM (Feedback Calibration Method)
FDFC
Fish
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Food Choice Motivations
Free Choice Profiling
Gin
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Hedonic
Highest Density Region
Ideal Product
Implicit Association Test
Imputation
In-Store Interviews
Incomplete Block Segmentation
Independent Components Analysis (ICA)
Individual Differences
Instructions
Joint Approximate Diagonalization of Eigenmatrices (JADE)
Just-About-Right (JAR)
Kombucha
L1-Norm
L1-Norm Principal Component Analysis (L1-Norm PCA)
Less
Light-Struck
Liking
Machine Learning
Meat
Median of Absolute Deviations (MAD)
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Multiple Factor Analysis (MFA)
A computational technique that separates multivariate signals into statistically independent components, applied in sensory science to decompose complex attribute patterns.
August 6, 2019
Investigating perception dynamics and uncertainty in temporal sensory data via independent components analysis (ICA)