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Opis

The effect of missing values on data classification is studied. A comparative analysis of data classification accuracy in different scenarios is presented. Several search techniques are considered in the study for feature selection and are applied to pre-process the dataset. The predictive performances of popular classifiers are compared quantitatively. The dataset is drawn from a breast cancer detection-decision context available at UCI machine learning repository. After analysing the experimental results,the work establishes the general concept of improved classification accuracy using missing values replacement.

Szczegóły książki

• Pełny tytuł: Missing Values in Data Mining
• Autor: Subhendu Pani
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 52
• EAN: 9783659753138
• ID: 16250771
• Wydawca: LAP Lambert Academic Publishing
• Waga: 96 g
• Wymiary: 220 × 150 × 3 mm
• Rok wydania: 2017

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