MultivariateSampleLogisticLinearRegression Method
Performs a linear logistic regression analysis.
Namespace: Meta.Numerics.StatisticsAssembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.2.0+6d77d64445f7d5d91b12e331399c4362ecb25333
public MultiLinearLogisticRegressionResult LogisticLinearRegression(
int outputIndex
)
Public Function LogisticLinearRegression (
outputIndex As Integer
) As MultiLinearLogisticRegressionResult
public:
MultiLinearLogisticRegressionResult^ LogisticLinearRegression(
int outputIndex
)
member LogisticLinearRegression :
outputIndex : int -> MultiLinearLogisticRegressionResult
- outputIndex Int32
- The index of the column to predict.
MultiLinearLogisticRegressionResultA logistic multi-linear model fit. The kth parameter is the slope of the multi-linear model with respect to
the kth column, except for k equal to the
outputIndex, for which it is the intercept.
Logistic linear regression is suited to situations where multiple input variables, either continuous or binary indicators, are used to predict
the value of a binary output variable. Like a linear regression, a logistic linear regression tries to find a model that predicts the output variable using
a linear combination of input variables. Unlike a simple linear regression, the model does not assume that this linear
function predicts the output directly; instead it assumes that this function value is then fed into a logit link function, which
maps the real numbers into the interval (0, 1), and interprets the value of this link function as the probability of obtaining success value
for the output variable.