Missing Values in Data Mining - Subhendu Pani
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Piegāde 15-21 darba dienu laikā
30 dienu atgriešanas politika
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 ... Pilns apraksts
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Aprašymas
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.
Vairāk informācijas
| Autors | Subhendu Pani |
|---|---|
| Izdevējs | LAP LAMBERT Academic Publishing |
| Izlaides gads | 2017 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783659753138 |