Examples of SquareRootFunction


Examples of org.apache.mahout.math.function.SquareRootFunction

      Vector delta = v.get().minus(sampleMean);
      sampleVar.assign(delta.times(delta), Functions.PLUS);
    }
    sampleVar = sampleVar.divide(sampleN - 1);
    sampleStd = sampleVar.clone();
    sampleStd.assign(new SquareRootFunction());
    log.info("Observing {} samples m=[{}, {}] sd=[{}, {}]",
             new Object[] { sampleN, sampleMean.get(0), sampleMean.get(1), sampleStd.get(0), sampleStd.get(1) });
  }
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Examples of org.apache.mahout.math.function.SquareRootFunction

    setNumObservations((long) getS0());
    setTotalObservations(getTotalObservations() + getNumObservations());
    setCenter(getS1().divide(getS0()));
    // compute the component stds
    if (getS0() > 1) {
      setRadius(getS2().times(getS0()).minus(getS1().times(getS1())).assign(new SquareRootFunction()).divide(getS0()));
    }
    setS0(0);
    setS1(center.like());
    setS2(center.like());
  }
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Examples of org.apache.mahout.matrix.SquareRootFunction

    }
    mean = s1.divide(s0);
    // compute the average of the component stds
    if (s0 > 1) {
      Vector std = s2.times(s0).minus(s1.times(s1)).assign(
          new SquareRootFunction()).divide(s0);
      stdDev = std.zSum() / s1.size();
    } else {
      stdDev = Double.MIN_VALUE;
    }
  }
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Examples of org.apache.mahout.matrix.SquareRootFunction

      return;
    }
    mean = s1.divide(s0);
    // compute the two component stds
    if (s0 > 1) {
      stdDev = s2.times(s0).minus(s1.times(s1)).assign(new SquareRootFunction())
          .divide(s0);
    } else {
      stdDev.assign(Double.MIN_NORMAL);
    }
  }
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Examples of org.apache.mahout.matrix.SquareRootFunction

  }

  /** @return the std */
  public double getStd() {
    Vector stds = pointSquaredTotal.times(getNumPoints()).minus(
          getPointTotal().times(getPointTotal())).assign(new SquareRootFunction())
          .divide(getNumPoints());
    return stds.zSum() / 2;
  }
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Examples of org.apache.mahout.matrix.SquareRootFunction

  /** Compute a "standard deviation" value to use as the "radius" of the cluster for display purposes */
  public double std() {
    if (s0 > 0) {
      Vector radical = s2.times(s0).minus(s1.times(s1));
      radical = radical.times(radical).assign(new SquareRootFunction());
      Vector stds = radical.assign(new SquareRootFunction()).divide(s0);
      return stds.zSum() / stds.size();
    } else {
      return 0;
    }
  }
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