Cross-Validation: Cross-validation is a technique used to assess a model's performance by dividing the dataset into multiple subsets. It helps evaluate how well a model generalizes to new data and can mitigate issues like overfitting. #TeamBasics #CrossVal
Overfitting: Overfitting occurs when a model learns to perform exceptionally well on the training data but fails to generalize to new, unseen data. It's a common problem when a model is overly complex or fits noise in the training data. Underfitting: Unde
Bias: In data analysis, bias refers to the presence of systematic errors or inaccuracies in data or modeling that consistently skew results away from the true values. It can result from various sources, including data collection, selection bias, or model a
Optimizing data routing and reliability in mesh networks, with a focus on community resilience, involves employing specific routing algorithms tailored to the unique challenges of community-driven scenarios. Here are some routing algorithms and their reaso