Table 1.

Some of the nodes available in MDP.

Node class name	Algorithm and Reference
PCANode	Principal Component Analysis (Jolliffe, 1986)
NIPALSNode	Nonlinear Iterative Partial Least Squares PCA (NIPALS) (Fritzke, 1995)
CuBICANode	Cumulant-based Independent Component Analysis (CuBICA) (Blaschke and Wiskott, 2004)
FastICANode	Independent Component Analysis (FastICA) (Hyvärinen, 1999)
JADENode	Cumulant-based Independent Component Analysis (JADE) (Cardoso, 1999)
TDSEPNode	Temporal blind-source separation algorithm (TDSEP) (Ziehe and Müller, 1998)
LLENode	Locally Linear Embedding Analysis (Roweis and Saul, 2000)
HLLENode	Hessian Locally Linear Embedding Analysis (Donoho and Grimes, 2003)
FDANode	Fisher Discriminant Analysis (Bishop, 1995)
SFANode	Slow Feature Analysis (Wiskott and Sejnowski, 2002)
ISFANode	Independent Slow Feature Analysis (Blaschke et al., 2007)
RBMNode	Restricted Boltzmann Machine (Hinton et al., 2006)
GrowingNeuralGasNode	Growing Neural Gas (learn a graph structure of the data) (Fritzke, 1995)
FANode	Factor Analysis (Bishop, 2007)
GaussianClassifierNode	Supervised gaussian classifier
PolynomialExpansionNode	Expand the signal in a polynomial space
TimeFramesNode	Expand the signal using a sliding temporal window (temporal embedding)
HitParadeNode	Record local minima and maxima in the signal
NoiseNode	Additive and multiplicative noise injection