trait Predictor extends AnyRef
The Predictor
trait provides a common framework for several predictors.
A predictor is for unbounded responses (real or integer). When the number
of distinct responses is bounded by some integer 'k', a classifier should
be used.
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abstract
def
fit: VectoD
Return the quality of fit including 'rSquared'.
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abstract
def
predict(z: VectoD): Double
Given a new continuous data vector z, predict the y-value of f(z).
Given a new continuous data vector z, predict the y-value of f(z).
- z
the vector to use for prediction
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abstract
def
train(): Unit
Given a set of data vectors 'x's and their corresponding responses 'y's, train the prediction function 'y = f(x)' by fitting its parameters.
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asInstanceOf[T0]: T0
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val
b: VectoD
Coefficient/parameter vector [b_0, b_1, ...
Coefficient/parameter vector [b_0, b_1, ... b_k]
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clone(): AnyRef
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def
coefficient: VectoD
Return the vector of coefficient/parameter values.
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val
e: VectoD
Residual/error vector [e_0, e_1, ...
Residual/error vector [e_0, e_1, ... e_m-1]
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def
fitLabels: Array[String]
Return the labels for the fit.
Return the labels for the fit. Override when necessary.
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getClass(): Class[_]
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hashCode(): Int
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def
notify(): Unit
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def
notifyAll(): Unit
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def
predict(z: VectorI): Double
Given a new discrete data vector z, predict the y-value of f(z).
Given a new discrete data vector z, predict the y-value of f(z).
- z
the vector to use for prediction
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def
residual: VectoD
Return the vector of residuals/errors.
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