Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection.
Isadora SallesPaola Mejia-DomenzainVinitra SwamyJulian BlackwellTanja KäserPublished in: AIED Companion (1) (2024)
Keyphrases
- feature selection
- learning process
- learning styles
- clustering algorithm
- unsupervised learning
- unsupervised feature selection
- clustering method
- k means
- high dimensionality
- data mining and pattern recognition
- data clustering
- information theoretic
- mutual information
- machine learning
- selecting features
- student learning
- hierarchical clustering
- learning environment
- categorical data
- neural network
- support vector
- self organizing maps
- cluster analysis
- feature extraction
- student model
- data sets
- feature selection algorithms
- feature weighting
- irrelevant features
- multi class
- classification models
- spectral clustering
- intelligent tutoring systems
- text categorization
- pairwise
- classification accuracy
- online learning
- data points