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Hyper-parameters tuning for SVM model | C, gamma, epsilon, kernel, GridsearchCV, RandomizedSearchCV
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Outline:
How to optimize the parameters of SVM model
How to find the optimum value for C, gamma, epsilon using GridsearchCV and RandomizedSearchCV
How to select kernel (polynomial, sigmoid, and radial basis function)
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The following important videos are recommended to watch:
#supportvectormachine #machinelearning #svm #supportvectormachines #supportvectormachinepython #supportvectormachineexplained
#svc #supervisedclassification #hyperparameter #parametrization #HowtofindtheoptimumvalueforCgammaepsilonusingGridsearchCVandRandomizedSearchCV
#Howtoselectkernelpolynomialsigmoidandradialbasisfunction
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Outline:
How to optimize the parameters of SVM model
How to find the optimum value for C, gamma, epsilon using GridsearchCV and RandomizedSearchCV
How to select kernel (polynomial, sigmoid, and radial basis function)
-----------------------------------------------------------------------------------------------------------------------------------
The following important videos are recommended to watch:
#supportvectormachine #machinelearning #svm #supportvectormachines #supportvectormachinepython #supportvectormachineexplained
#svc #supervisedclassification #hyperparameter #parametrization #HowtofindtheoptimumvalueforCgammaepsilonusingGridsearchCVandRandomizedSearchCV
#Howtoselectkernelpolynomialsigmoidandradialbasisfunction