Searched defs:regression (Results 1 - 13 of 13) sorted by relevance

/external/testng/src/test/java/test/regression/
H A DBeforeTestFailingTest.java1 package test.regression;
H A DMyTestngTest.java1 package test.regression;
H A DMyTestngTest2.java1 package test.regression;
/external/testng/src/test/java/test/regression/groupsordering/
H A DA.java1 package test.regression.groupsordering;
H A DB.java1 package test.regression.groupsordering;
H A DBase.java1 package test.regression.groupsordering;
/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/
H A DMultipleLinearRegression.java17 package org.apache.commons.math.stat.regression;
20 * The multiple linear regression can be represented in matrix-notation.
25 * <b>regressors</b>, b is <code>k-vector</code> of <b>regression parameters</b> and <code>u</code> is an <code>n-vector</code>
36 * Estimates the regression parameters b.
43 * Estimates the variance of the regression parameters, ie Var(b).
64 * Returns the standard errors of the regression parameters.
66 * @return standard errors of estimated regression parameters
H A DGLSMultipleLinearRegression.java17 package org.apache.commons.math.stat.regression;
25 * The GLS implementation of the multiple linear regression.
H A DOLSMultipleLinearRegression.java17 package org.apache.commons.math.stat.regression;
30 * multiple linear regression model.</p>
32 * <p>The regression coefficients, <code>b</code>, satisfy the normal equations:
67 * compatible for the regression
175 * <p>If the regression is estimated without an intercept term, what is returned is <pre>
205 * Calculates the regression coefficients using OLS.
215 * <p>Calculates the variance-covariance matrix of the regression parameters.
H A DAbstractMultipleLinearRegression.java17 package org.apache.commons.math.stat.regression;
42 /** Whether or not the regression model includes an intercept. True means no intercept. */
66 * <code>nobs = 3</code> and <code>nvars = 2</code> creates a regression dataset with two
195 * sufficient data to estimate regression coefficients for each of the
300 * Estimates the standard error of the regression.
302 * @return regression standard error
310 * Calculates the beta of multiple linear regression in matrix notation.
317 * Calculates the beta variance of multiple linear regression in matrix
352 * Calculates the residuals of multiple linear regression in matrix
H A DSimpleRegression.java18 package org.apache.commons.math.stat.regression;
29 * Estimates an ordinary least squares regression model
46 * different x coordinates are requred to estimate a bivariate regression
125 * Adds the observation (x,y) to the regression data set.
161 * Removes the observation (x,y) from the regression data set.
164 * SimpleRegression instances in streaming mode where the regression
220 * streaming mode where the regression is applied to a sliding "window" of
278 * Returns the intercept of the estimated regression line.
291 * @return the intercept of the regression line
298 * Returns the slope of the estimated regression lin
[all...]
/external/opencv/ml/include/
H A Dml.h310 bool regression; member in class:CvKNearest
/external/opencv3/apps/traincascade/
H A Dold_ml.hpp282 bool regression; member in class:CvKNearest
1276 // class_count == 1 in the case of regression,
1295 // problem: regression
1299 // problem: regression
1303 // problem: regression
1707 // Is it a regression or a classification.
1716 // true - if regression.

Completed in 2508 milliseconds