👉 Fuzziness is a concept in artificial intelligence and machine learning that refers to the degree to which an input data set contains noise or uncertainty. In other words, it measures how much the data can be distorted by outliers, missing values, or other sources of variation. Fuzziness helps in creating models that are more robust, reliable, and interpretable when dealing with noisy data.
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What is the definition of Fuzzines? 🙋
👉 Fuzzines are a type of noise that is generated by artificial intelligence and computer systems. They are typically used to simulate human behavior or to test algorithms, but they can also be used for malicious purposes such as generating false positive results in automated testing. Fuzzing can be done through various techniques, including random number generation, binary string manipulation, and data injection attacks.
