Input
SQL Call
DROP TABLE densesvm_iris_sigmoid_model;
SELECT * FROM SVMDense (
ON svm_iris_train AS InputTable
OUT TABLE ModelTable (densesvm_iris_sigmoid_model)
USING
IDColumn ('id')
TargetColumns ('[1:4]')
ResponseColumn ('species')
RegularizationLambda (1)
Bias (0)
KernelFunction ('sigmoid')
Gamma (0.1)
HashBits (512)
SubspaceDimension (120)
MaxIterNum (30)
Seed (1)
) AS dt;
Output
message ----------------------------------------------------------------------------------------------------------------------------------------- Model table is created successfully The model is trained with 120 samples and 512 unique attributes with hash projection There are 3 different classes in the training set The model is converged after 12 steps with epsilon 0.01, the average value of the loss function for the training set is 56.53662594767713 The corresponding training parameters are cost:1.0 bias:0.0
Only models with RBF and Sigmoid kernels have converged. This may mean that the true boundaries in the data set are hard to capture with a linear or polynomial model.
Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.