Sep 20, 2024 ¡¤ We conclude that CQI can be a suitable approach for the imputation of systematically missing data when data from multiple studies cannot be pooled.

Sep 23, 2024 ¡¤ The aim of this work is to analyze the missing data problem in pattern classification tasks, and to summarize and compare some of the well-known methods used ...

Sep 30, 2024 ¡¤ This method leverages the low-dimensional subspace structure of the data to estimate missing values through a linear combination of observed values, thus ...

Oct 1, 2024 ¡¤ With the sparse data representation and compatibility with non-negative data of NMF algorithm, the missing parts of label matrix can be predicted [9].

5 days ago ¡¤ It operates by identifying the 'k' closest data points to a missing value and using their attributes to estimate the missing data.

Sep 23, 2024 ¡¤ The fundamental idea is to estimate the heritability due to common variants by studying the extent to which the phenotypic similarity across pairs of ...

Sep 20, 2024 ¡¤ This article provides a tutorial on the causal analysis of human behavior using smartphone sensor data by reviewing well-known matching methods.

Sep 22, 2024 ¡¤ In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM).