| Class and Description |
|---|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| GaussianVectorNaiveBayesModel
An implementation of a
EstimatableModel that uses a
VectorNaiveBayesCategorizer to associate vectors (actually double[])
with a category based on the naive bayes model. |
| LeastSquaresLinearModel
Model of mapping between pairs of integers learned from a least-squares
regression.
|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| UnivariateGaussianNaiveBayesModel
An implementation of a
EstimatableModel that uses a
VectorNaiveBayesCategorizer to associate a univariate (a
Double) with a category. |
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|
| Class and Description |
|---|
| EstimatableModel
An extension to a
Model that allows the model to be estimated from a
series of observations of both the independent and dependent variables. |
| Model
The Model interface defines a mathematical model which links dependent and
independent variables.
|