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ML models for User Recognition using Keystroke Dynamics The keystroke dynamics that are used in this article’s machine learning models for user recognition are behavioral biometrics. Keystroke dynamics use the distinctive way that each person types to confirm their identity. This is accomplished by analyzing the on Key-Press and Key-Release — that make up a keystroke on computer keyboards to extract typing patterns.
DataFrame return data_df All the code you can find on my GitHub in the KeystrokeDynamics repository: https://github.com/BogdanAlinTudorache/KeystrokeDynamics?embedable=true Train the MLs Now that we have parsed the data we can start building the models by training the MLs. Support Vector Machine def train_svm: import joblib from sklearn.
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