Tweet Sentiment Visualization and Classification Using Manifold Dimensionality Reduction.
Francisco GrimaldoEmilia López-IñestaJuan José Garcés-IniestaJuan Gómez-SanchísDaniel García-CostaEusebio Marqués-BenítezEmilio Soria-OlivasPublished in: CCIA (2018)
Keyphrases
- dimensionality reduction
- feature extraction
- feature space
- sentiment analysis
- low dimensional
- high dimensionality
- high dimensional
- pattern recognition
- manifold learning
- classification accuracy
- feature selection
- dimensionality reduction methods
- text classification
- image classification
- kernel learning
- polarity classification
- lower dimensional
- multidimensional scaling
- nonlinear dimensionality reduction
- machine learning
- support vector
- social media
- feature vectors
- supervised learning
- supervised dimensionality reduction
- support vector machine svm
- data representation
- data sets
- feature set
- pattern recognition and machine learning
- diffusion maps
- locally linear embedding
- decision trees
- training set
- principal components
- pattern classification
- data points
- support vector machine
- class labels
- high dimensional data
- information extraction
- principal component analysis