Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td align="left">Variables</td><td align="left">Description</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td align="left">Number of cases</td><td align="left">Number of records in the dataset</td></tr><tr><td align="left">Number of attributes </td><td align="left">Number of features characteristic of the dataset</td></tr><tr><td align="left">Degree of class imbalance</td><td align="left">Ratio </td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Mathematical Problems in Engineering

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Table 2

Table 2: Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications 

Table 2 | Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications 