I am using "fitcdiscr" function from the Statistics and Machine Learning Toolbox and I have the following questions on how to use the options for the "fitcdiscr" function
1) How do I obtain weights for the trained model to calculate the projected space ?
2) Is there any way to hide the training output in command terminal?
3) Does providing ‘OptimizeHyperparameters’, ‘auto’ name-value pair to train the model on the hyperparameters update gamma and delta iteratively or do we need to train the model with the obtained hyperparameters once more to obtain valid results ?
4) Does training model followed with ‘cvshrink’ regularization and training model with inbuilt optimization yield same results ? Is either of them computationally intensive than the other?I am using "fitcdiscr" function from the Statistics and Machine Learning Toolbox and I have the following questions on how to use the options for the "fitcdiscr" function
1) How do I obtain weights for the trained model to calculate the projected space ?
2) Is there any way to hide the training output in command terminal?
3) Does providing ‘OptimizeHyperparameters’, ‘auto’ name-value pair to train the model on the hyperparameters update gamma and delta iteratively or do we need to train the model with the obtained hyperparameters once more to obtain valid results ?
4) Does training model followed with ‘cvshrink’ regularization and training model with inbuilt optimization yield same results ? Is either of them computationally intensive than the other? I am using "fitcdiscr" function from the Statistics and Machine Learning Toolbox and I have the following questions on how to use the options for the "fitcdiscr" function
1) How do I obtain weights for the trained model to calculate the projected space ?
2) Is there any way to hide the training output in command terminal?
3) Does providing ‘OptimizeHyperparameters’, ‘auto’ name-value pair to train the model on the hyperparameters update gamma and delta iteratively or do we need to train the model with the obtained hyperparameters once more to obtain valid results ?
4) Does training model followed with ‘cvshrink’ regularization and training model with inbuilt optimization yield same results ? Is either of them computationally intensive than the other? fitcdiscr, options, weights, coeffs, verbose, optimizehyperparameters, cvshrink MATLAB Answers — New Questions
