the first 50000 samples of MNIST will be used for training, the next 10000 for validation,...

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the first 50000 samples of MNIST will be used for training, the next 10000 for validation, and the last 10000 for testing. 1. Logistic regression with L2 penalty term with C= 10%, n=-10:1:10. • For each C, generate a model for O-detector, and determine the F score using the validation dataset. • According to the F₁ scores, determine the optimal C value. Apply the corresponding model to the testing dataset and report the following metrics • testing accuracy • F₁ score ▪ ROC curve • the area under the curve 2. Logistic regression with L1 penalty term with C= 10, n--10:1:10. • For each C, generate a model for O-detector, and determine the F score using the validation dataset. • According to the F₁ scores, determine the optimal C value. Apply the corresponding model to the testing dataset and report the following metrics • testing accuracy ▪ F₁ score • ROC curve the area under the curve the first 50000 samples of MNIST will be used for training, the next 10000 for validation, and the last 10000 for testing. 1. Logistic regression with L2 penalty term with C= 10%, n=-10:1:10. • For each C, generate a model for O-detector, and determine the F score using the validation dataset. • According to the F₁ scores, determine the optimal C value. Apply the corresponding model to the testing dataset and report the following metrics • testing accuracy • F₁ score ▪ ROC curve • the area under the curve 2. Logistic regression with L1 penalty term with C= 10, n--10:1:10. • For each C, generate a model for O-detector, and determine the F score using the validation dataset. • According to the F₁ scores, determine the optimal C value. Apply the corresponding model to the testing dataset and report the following metrics • testing accuracy ▪ F₁ score • ROC curve the area under the curve

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1 Logistic Regression with L2 Penalty Ridge and Different C Values a For each C generate a model for Odetector and determine the F score using the validation dataset Logistic regression with L2 penalt... View the full answer