Missing Values in Data Mining - Subhendu Pani
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Toimitus 15-21 arkipäivässä
30 päivän palautusoikeus
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-de ... Täydellinen kuvaus
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Kuvaus
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.
Lisätietoja
| Kirjoittaja | Subhendu Pani |
|---|---|
| Julkaisija | LAP LAMBERT Academic Publishing |
| Julkaisuvuosi | 2017 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783659753138 |