abstract class GeneralizedLinearModel extends Serializable
GeneralizedLinearModel (GLM) represents a model trained using GeneralizedLinearAlgorithm. GLMs consist of a weight vector and an intercept.
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def
predictPoint(dataMatrix: Vector, weightMatrix: Vector, intercept: Double): Double
Predict the result given a data point and the weights learned.
Predict the result given a data point and the weights learned.
- dataMatrix
Row vector containing the features for this data point
- weightMatrix
Column vector containing the weights of the model
- intercept
Intercept of the model.
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val
intercept: Double
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def
predict(testData: Vector): Double
Predict values for a single data point using the model trained.
Predict values for a single data point using the model trained.
- testData
array representing a single data point
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Double prediction from the trained model
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def
predict(testData: RDD[Vector]): RDD[Double]
Predict values for the given data set using the model trained.
Predict values for the given data set using the model trained.
- testData
RDD representing data points to be predicted
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RDD[Double] where each entry contains the corresponding prediction
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def
toString(): String
Print a summary of the model.
Print a summary of the model.
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val
weights: Vector
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