Machine learning explainability ensures that AI models are transparent, trustworthy and accurate Explainability enables data scientists to understand how and why an AI model arrived at a particular decision or prediction SHAP values are a powerful tool for explainability as they provide a way to measure the contribution of each feature in a model to the final prediction, … [Read more...] about AI Decision Making with SHAP Values
SHAP
How CrowdStrike Enhances Machine Learning with SHAP
At CrowdStrike®, machine learning is a major tool for detecting new malware families and keeping our customers safe. We utilize gradient boosted trees with thousands of features to classify whether a file sample is labeled as malware or clean. This model provides a lot of predictive power, leading to a high level of accuracy, but as a tradeoff, it is challenging to comprehend … [Read more...] about How CrowdStrike Enhances Machine Learning with SHAP