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Showing 1 to 4 of 4 for “"machine learning ensembles"”.

  1. Operating System Identification by IPv6 Communication using Machine Learning Ensembles

    … databases, very little work has focused on using machine learning techniques. Moreover, significantly more work has focused on IPv4 than IPv6. We introduce a collaborative neural network ensemble that uses a unique voting system and a random forest ensemble to deliver accurate predictions. This …

    arkansas Repository record for Operating System Identification by IPv6 Communication using Machine Learning Ensembles (opens in a new tab)

  2. Cognitive and Behavioral Model Ensembles for Autonomous Virtual Characters

    … appropriately a character performed and through machine learning the system is able to determine how the character should act given the current situation. Empirical results from multiple case studies validate the approach taken.

    byu Repository record for Cognitive and Behavioral Model Ensembles for Autonomous Virtual Characters (opens in a new tab)

  3. Heuristic Weighted Voting

    <p>Selecting an effective method for combining the votes of classifiers in an ensemble can have a significant impact on the overall classification accuracy an ensemble is able to achieve. With some methods, the ensemble cannot even achieve as high a classification accuracy as the most accurate …

    byu Repository record for Heuristic Weighted Voting (opens in a new tab)

  4. Combinación de clasificadores: construcción de características e incremento de la diversidad

    Los multiclasificadores son actualmente un área de interés dentro del Reconocimiento de Patrones. En esta tesis se presentan tres métodos multiclasificadores: "Cascadas para datos nominales", "Disturbing Neighbors" y "Random Feature Weights". Las Cascadas permiten que clasificadores que necesitan …

    burgos Repository record for Combinación de clasificadores: construcción de características e incremento de la diversidad (opens in a new tab)