nuget
Procedures
01 Syntax
Microsoft.VisualBasic.MachineLearning.SVM.Procedures
02 Methods
| Name | Overloads | Summary |
|---|---|---|
| sigmoid_train | 1 | Platt's binary SVM Probablistic Output: an improvement from Lin et al. |
| multiclass_probability | 1 | Method 2 from the multiclass_prob paper by Wu, Lin, and Weng |
| svm_binary_svc_probability | 1 | Cross-validation decision values for probability estimates |
| svm_svr_probability | 1 | Return parameter of a Laplace distribution |
| svm_group_classes | 1 | group training data of the same class |
| oneClassSvm | 1 | regression or one-class-svm |
| multipleClassification | 1 | classification |
| svm_cross_validation | 1 | Stratified cross validation |
| svm_predict | 1 |
03 Members
sigmoid_train(
Int32, Double(), ColorClass(), Double())Platt's binary SVM Probablistic Output: an improvement from Lin et al.
Parameters
| Name | Type | Description |
|---|---|---|
l | Int32 | - |
dec_values | Double() | - |
labels | ColorClass() | - |
probAB | Double() | - |
multiclass_probability(
Int32, Double[0:,0:], Double())Method 2 from the multiclass_prob paper by Wu, Lin, and Weng
Parameters
| Name | Type | Description |
|---|---|---|
k | Int32 | - |
r | Double[0:,0:] | - |
p | Double() | - |
Cross-validation decision values for probability estimates
Parameters
Return parameter of a Laplace distribution
Parameters
group training data of the same class
Parameters
| Name | Type | Description |
|---|---|---|
prob | Problem | - |
nr_class_ret | Int32 | - |
label_ret | Int32() | label name |
start_ret | Int32() | begin of each class |
count_ret | Int32() | #data of classes |
perm | Int32() | indices to the original data, perm, length l, must be allocated before calling this subroutine |
regression or one-class-svm
Parameters
classification
Parameters
Stratified cross validation
Parameters
Parameters
Returns
兼容分类以及打分这两种工作模式