Feedback Request
FINDHR
Veranderingen op "8"
Titel
- -{"en"=>""}
- +{"en"=>"8"}
Body
- -[""]
- +["- World - Data: when biases from the real world percolate into the data (e.g. historical bias, selection bias or technosolution bias).\n- Data - Population: when biases are produced by the data, the most classic example is labelling errors.\n- Population - Sample: when the population is not well represented in the sample (e.g. population bias, survey bias, seasonal bias, etc.).\n- Sample - Variables and values: when the data of the sample is not well represented by the values or the variables (e.g. oversimplification problem, omitted variable, etc.).\n- Variables and values - Patterns: when the data used can mislead patterns or assumptions (e.g. measurement bias, over and underfitting, etc.)\n- Patterns - Predictions: when the resulting patterns of the analysis suggest outcomes that can be biased or incorrectly adapted to the real world (e.g. aggregation bias, model selection problems, etc.).\n- Predictions - Decisions: when the analysis obtained mislead decisions in the real world (e.g. visualization errors). \nDecisions - World: when the decisions made by the algorithm affect the real-world application and use of the algorithm (e.g. automation bias, accessibility, etc.).\n"]