Machine learning : SVM
SVM - Support Vector machines.
Different kernels - linear, rbf, poly etc.
Each Kernel is an additional parameter to SVM classifier to map data points to ta new dimensional space and then perform the classification.
Gamma more = ?
C value is more means that the error is more => More data points are correctly classified.
More the value of C does not gurantee an accurate classifier.
One needs to be careful of overfitting in machine learning.
For SVM overfitting the parameters in control are C, gamma, kernel used.
Different kernels - linear, rbf, poly etc.
Each Kernel is an additional parameter to SVM classifier to map data points to ta new dimensional space and then perform the classification.
Gamma more = ?
C value is more means that the error is more => More data points are correctly classified.
More the value of C does not gurantee an accurate classifier.
One needs to be careful of overfitting in machine learning.
For SVM overfitting the parameters in control are C, gamma, kernel used.
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