class Spark::Mllib::RegressionModel

RegressionModel

A linear model that has a vector of coefficients and an intercept.

Attributes

intercept[R]
weights[R]

Public Class Methods

new(weights, intercept) click to toggle source
# File lib/spark/mllib/regression/common.rb, line 12
def initialize(weights, intercept)
  @weights = Spark::Mllib::Vectors.to_vector(weights)
  @intercept = intercept.to_f
end

Public Instance Methods

predict(data) click to toggle source

Predict the value of the dependent variable given a vector data containing values for the independent variables.

Examples:

lm = RegressionModel.new([1.0, 2.0], 0.1)

lm.predict([-1.03, 7.777]) - 14.624 < 1e-6
# => true

lm.predict(SparseVector.new(2, {0 => -1.03, 1 => 7.777})) - 14.624 < 1e-6
# => true
# File lib/spark/mllib/regression/common.rb, line 29
def predict(data)
  data = Spark::Mllib::Vectors.to_vector(data)
  @weights.dot(data) + @intercept
end