👉 In computer science, "robustness" refers to a property that a system or component is able to withstand failures and adversarial inputs. It involves the ability of an object or system to perform well in various circumstances without experiencing significant degradation or failure. This can be achieved through several techniques such as hardware design, software optimization, and user testing. In other words, robustness refers to the property of a system or component that allows it to function effectively even when faced with unexpected events or failures.
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What is the definition of Robustiously? 🙋
👉 Robustly is a term used in statistics and machine learning to describe an attribute that is resistant to outliers, extreme values, or other types of anomalies. It refers to an attribute that has a high degree of variability without being subject to systematic errors, such as those caused by random fluctuations or other factors beyond the control of the model. In statistics, robustly defined attributes can be used in machine learning models to ensure that they are not influenced by outliers or extreme values, which can lead to inaccurate
What is the definition of Robustious? 🙋
👉 Robust refers to a property or quality that is characterized by its adaptability and resilience, often associated with stability and safety. It can also refer to the ability of something to withstand or withstand various conditions without breaking or failing. In the context of machine learning, robustness refers to how well an algorithm handles different types of inputs and outputs.
