The dense SVM linear model is similar to the model created by the sparse SVM function.
SQL Call
DROP TABLE densesvm_iris_linear_model;
SELECT* FROM SVMDense (
ON svm_iris_train AS InputTable
OUT TABLE ModelTable (densesvm_iris_linear_model)
USING
IDColumn ('id')
InputColumns ('[1:4]')
ResponseColumn ('species')
Cost (1)
Bias (0)
KernelFunction ('linear')
MaxStep (100)
Seed (1)
) AS dt;
Output
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Model table is created successfully The model is trained with 120 samples and 4 unique attributes There are 3 different classes in the training set The model is not converged after 100 steps with epsilon 0.01, the average value of the loss function for the training set is 39.630857206982405 The corresponding training parameters are cost:1.0 bias:0.0 |