**Input** | Input | Input Values [x lists (x = number of training samples) of y numbers (y = dimensionality of sample input); Input and Output can be one or many dimensional, and the number of dimensions can be different] | Number |

**Output** | Output | Output Values [x lists (x = number of training samples) of z numbers (z = dimensionality of sample output); Input and Output can be one or many dimensional, and the number of dimensions can be different] | Number |

**Layers** | Layers | Hidden Layer Count | Integer |

**Nodes** | Nodes | Node Count per Hidden Layer, 0 = Maximum of Input and Output Dimensionality | Integer |

**Seed** | Seed | Random Seed | Integer |

**SeedNet** | SeedNet | Seed Network to continue training on it; a seed model overrides the internal model which is saved between updates of the component if 'reset' is false. | Network oSL |

**On** | On | Switch Off to not calculate anything. | Boolean |

**Settings** | Settings | Settings for the Learning process | RPROP Learning Settings |