MLP_Train
Creates and trains multilayer perceptron classifier.
Syntax
C++
C#
Python
def MLP_Train( inMlpModel: MlpModel, inInputVectorArray: list[ list[float] ], inResponseVectorArray: list[ list[float] ], outMlpModel: MlpModel, /, *, inTestInputVectorArray: list[ list[float] ] | None = None, inTestResponseVectorArray: list[ list[float] ] | None = None, inIterationCount: int = 100, inLearningRate: float = 1.0, inMomentum: float = 0.01, inRandomSeed: int | None = None, diagErrorChartLearning: Profile | None = None, diagErrorChartTesting: Profile | None = None ) -> None
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
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inMlpModel | MlpModel | Initialized MLP model | ||
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inInputVectorArray | list[ list[float] ] | Array of features used to train model | ||
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inResponseVectorArray | list[ list[float] ] | Array of answers which classifier should get. | ||
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inTestInputVectorArray | list[ list[float] ] | None | None | Array of features used to test classifier during training process | |
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inTestResponseVectorArray | list[ list[float] ] | None | None | Array of answers used to test classifier during training process | |
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inIterationCount | int | 1 - ![]() |
100 | Learning iteration count |
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inLearningRate | float | 0.01 - 1.0 | 1.0 | Learning factor |
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inMomentum | float | 0.0 - 1.0 | 0.01 | Learning momentum ratio |
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inRandomSeed | int | None | 0 - ![]() |
None | Number used as starting random seed |
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outMlpModel | MlpModel | Trained MlpModel | ||
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diagErrorChartLearning | Profile | None | None | Mean error of testing results data during learning process | |
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diagErrorChartTesting | Profile | None | None | Mean error during learning process |




