Bias (ethics/fairness): Revision history

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17 March 2023

18 February 2023

  • curprev 12:1312:13, 18 February 2023‎ Alpha5 talk contribs‎ 3,376 bytes +12‎ No edit summary
  • curprev 12:1012:10, 18 February 2023‎ Alpha5 talk contribs‎ 3,364 bytes +109‎ No edit summary
  • curprev 12:0512:05, 18 February 2023‎ Alpha5 talk contribs‎ 3,255 bytes +3,255‎ Created page with "==Introduction== Bias in machine learning refers to systematic errors or discrimination present in a model's predictions or decisions. It can arise when the data used to train the model is not representative of the population it will be applied to, or certain groups are disproportionately represented or excluded from training data. ==Sources of bias in machine learning== Biases can arise during the creation and deployment of machine learning models. 1. Data Bias: This..."
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