Whodunit: Cyber-attack attribution
Part 2: How to evaluate the classifiers with an imbalanced dataset In Part 2, before evaluating the pipelines developed with IBM AutoAI, we need to review the metrics for evaluating imbalanced datasets. Imbalanced data analysis For imbalanced classification problems, the majority class is typically referred to as the negative outcome (e.g., such as “nonstate”), and the minority class is typically referred to as the…
Whodunit: Cyber-attack attribution Part 2: How to evaluate the classifiers with an imbalanced dataset In Part 2, before evaluating the pipelines developed with IBM AutoAI, we need to review the metrics for evaluating imbalanced datasets. Imbalanced data analysis For imbalanced classification problems, the majority class is typically referred to as the negative outcome (e.g., such as “nonstate”), and the minority class is typically referred to as the… machine-learning
Whodunit Cyberattack attribution Part 2 evaluate classifier imbalanced dataset Part 2 evaluating pipeline developed IBM AutoAI need review metric evaluating imbalanced datasets Imbalanced data analysis imbalanced classification problem majority class typically referred negative outcome eg “nonstate” minority class typically referred the… machinelearning