Research Article
Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications
Table 11
Factors influencing accuracy (RMSE) for each algorithm (standard beta coefficient): -MEANS_CLUSTERING.
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Note 1: N_attributes: number of attributes, N_cases: number of cases, C_imbalance: degree of class imbalance, R_missing: missing data ratio, SE_HS: horizontal scatteredness, SE_VS: vertical scatteredness, spread: missing data spread, and missing patterns: univariate (P_missing_dum1 = 1, P_missing_dum2 = 0), monotone (P_missing_dum1 = 0, P_missing_dum2 = 1), and arbitrary (P_missing_dum1 = 1, P_missing_dum2 = 1) Note 2: RMSE indicates error; therefore, lower values are better. Note 3: * < 0.05, ** < 0.01. |