/** * Creates a new instance of LinearRegression * @param regularization * L2 ridge regularization term, must be nonnegative, a value of zero is * equivalent to unregularized regression. * @param usePseudoInverse * Flag to use a pseudoinverse. True to use the expensive, but more * accurate, pseudoinverse routine. False uses a very fast, but * numerically less stable LU solver. Default value is "true". */ public LinearRegression( double regularization, boolean usePseudoInverse ) { this.setRegularization(regularization); this.setUsePseudoInverse(usePseudoInverse); }
/** * Creates a new instance of LinearRegression * @param regularization * L2 ridge regularization term, must be nonnegative, a value of zero is * equivalent to unregularized regression. * @param usePseudoInverse * Flag to use a pseudoinverse. True to use the expensive, but more * accurate, pseudoinverse routine. False uses a very fast, but * numerically less stable LU solver. Default value is "true". */ public LinearRegression( double regularization, boolean usePseudoInverse ) { this.setRegularization(regularization); this.setUsePseudoInverse(usePseudoInverse); }
/** * Creates a new instance of LinearRegression * @param regularization * L2 ridge regularization term, must be nonnegative, a value of zero is * equivalent to unregularized regression. * @param usePseudoInverse * Flag to use a pseudoinverse. True to use the expensive, but more * accurate, pseudoinverse routine. False uses a very fast, but * numerically less stable LU solver. Default value is "true". */ public LinearRegression( double regularization, boolean usePseudoInverse ) { this.setRegularization(regularization); this.setUsePseudoInverse(usePseudoInverse); }
linear.setUsePseudoInverse(this.getUsePseudoInverse()); LinearDiscriminant weights = linear.learn(vectorData); return new VectorFunctionLinearDiscriminant<InputType>(
linear.setUsePseudoInverse(this.getUsePseudoInverse()); LinearDiscriminant weights = linear.learn(vectorData); return new VectorFunctionLinearDiscriminant<InputType>(
linear.setUsePseudoInverse(this.getUsePseudoInverse()); LinearDiscriminant weights = linear.learn(vectorData); return new VectorFunctionLinearDiscriminant<InputType>(