Forecasting high-dimensional dynamics exploiting suboptimal embeddings.
Shunya OkunoKazuyuki AiharaYoshito HirataPublished in: CoRR (2019)
Keyphrases
- high dimensional
- low dimensional
- dimensionality reduction
- high dimensional data
- manifold learning
- low dimensional spaces
- euclidean space
- data points
- vector space
- parameter space
- feature space
- multi dimensional
- sparse data
- dynamic model
- input space
- dynamical systems
- short term
- high dimensionality
- computationally efficient
- dimension reduction
- forecasting model
- exchange rate
- support vector
- principal component analysis
- grey model
- forecasting accuracy
- high dimensional problems
- autoregressive model
- high dimension
- electricity markets
- lower dimensional
- variable selection
- similarity search
- nearest neighbor
- metric space
- sparse coding
- neural network
- microarray data