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Sklearn MLP Neural Network

Multi-layer Perceptron neural network using scikit-learn

Actions2

Predict

AI-generated

Summary

Predict using a trained MLP model.

Inputs

  • modelType — Choice of model type (Classifier or Regressor)
  • modelData (required) — JSON string containing the trained model
  • predictFeatureColumns (required) — Comma-separated list of feature column names
  • pythonPath — Path to Python executable with scikit-learn installed

Output shape

a list of prediction records

Each record includes the original input plus a prediction field; for classification models also a probabilities field; may include additional metadata such as model_type and score.

Examples

Example 1: Classify iris flower species

Model Type = Classifier, Model Data = '', Feature Columns = 'sepal_length,sepal_width,petal_length,petal_width', Python Path = 'python3'

Example 2: Predict continuous target values

Model Type = Regressor, Model Data = '', Feature Columns = 'feature1,feature2,feature3', Python Path = 'python3'

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