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Showing 1 to 4 of 4 for “"Unbalanced Datasets"”.

  1. A Comparison of Image Classification with Different Activation Functions in Balanced and Unbalanced Datasets

    … performance in balanced or imbalanced datasets. Our analysis evaluates various network architectures for both commonly used and novel datasets and presents a comprehensive analysis of ten widely used activation functions. The experimental results show that the swish and softplus …

    vt Repository record for A Comparison of Image Classification with Different Activation Functions in Balanced and Unbalanced Datasets (opens in a new tab)

  2. CLASSIFIERS BASED ON A NEW APPROACH TO ESTIMATE THE FISHER SUBSPACE AND THEIR APPLICATIONS

    … to deal with high dimensional and highly unbalanced datasets whose cardinality is low. The efficacy of the proposed techniques has been proved by the results achieved on real and synthetic datasets, and by the comparison with state of the art predictors.

    milano Repository record for CLASSIFIERS BASED ON A NEW APPROACH TO ESTIMATE THE FISHER SUBSPACE AND THEIR APPLICATIONS (opens in a new tab)

  3. Risk stratification of cardiovascular patients using a novel classification tree induction algorithm with non-symmetric entropy measures

    … build risk stratification models that can handle unbalanced datasets and improve risk stratification. We propose a novel classification tree induction algorithm that uses non-symmetric entropy measures to construct classification trees. We apply our methods to the application of identifying …

    mit Repository record for Risk stratification of cardiovascular patients using a novel classification tree induction algorithm with non-symmetric entropy measures (opens in a new tab)

  4. Enhancing Telecom Churn Prediction: Adaboost with Oversampling and Recursive Feature Elimination Approach

    <p>Churn prediction is a critical task for businesses to retain their valuable customers. This paper presents a comprehensive study of churn prediction in the telecom sector using 15 approaches, including popular algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random …

    calpoly Repository record for Enhancing Telecom Churn Prediction: Adaboost with Oversampling and Recursive Feature Elimination Approach (opens in a new tab)