@Test public void testPenDigits() { System.out.println("Pen Digits"); MathEx.setSeed(19650218); int[] prediction = CrossValidation.classification(10, PenDigits.x, PenDigits.y, (x, y) -> RDA.fit(x, y, 0.9)); int error = Error.of(PenDigits.y, prediction); System.out.println("Error = " + error); assertEquals(103, error); }
public static RDA fit(Formula formula, DataFrame data) { return fit(formula, data, new Properties()); }
RDA extends QDA { public static RDA fit(Formula formula, DataFrame data) { return fit(formula, data, new Properties()); } }
RDA extends QDA { public static RDA fit(Formula formula, DataFrame data) { return fit(formula, data, new Properties()); } RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling);  RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling, IntSet labels); }
RDA extends QDA { public static RDA fit(Formula formula, DataFrame data) { return fit(formula, data, new Properties()); } RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling);  RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling, IntSet labels); static RDA fit(Formula formula, DataFrame data); static RDA fit(Formula formula, DataFrame data, Properties prop); static RDA fit(double[][] x, int[] y, Properties prop); static RDA fit(double[][] x, int[] y, double alpha); static RDA fit(double[][] x, int[] y, double alpha, double[] priori, double tol); }
RDA extends QDA { public static RDA fit(Formula formula, DataFrame data) { return fit(formula, data, new Properties()); } RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling);  RDA(double[] priori, double[][] mu, double[][] eigen, Matrix[] scaling, IntSet labels); static RDA fit(Formula formula, DataFrame data); static RDA fit(Formula formula, DataFrame data, Properties prop); static RDA fit(double[][] x, int[] y, Properties prop); static RDA fit(double[][] x, int[] y, double alpha); static RDA fit(double[][] x, int[] y, double alpha, double[] priori, double tol);  }