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') InputColumns ('[1:4]') ResponseColumn ('species') Cost (1) Bias (0) KernelFunction ('sigmoid') Gamma (0.1) HashBits (512) SubspaceDimension (120) MaxStep (30) Seed (1) ) AS dt;
Output
message |
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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 18 steps with epsilon 0.01, the average value of the loss function for the training set is 55.832581089711596 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.