Imputasi Biclustering Berbasis Shifting-and-Scaling Similarity (SSSim) Menggunakan Regresi Kuantil Ke-t (NCBI-SSSim-tQR) pada Data Ekspresi Gen = Shifting-and-Scaling Similarity (SSSim)-Based Biclustering Imputation Using t-th Quantile Regression (NCBI-SSSim-tQR) on Gene Expression Data

Metode Biclustering Terurut Berbasis k-Nearest Neighbour, Mean Square Residual, dan Jarak Euclidean dalam Imputasi Missing Values pada Data Ekspresi Gen = Sequential Biclustering Method Based on k-Nearest Neighbor, Mean Squared Residual, and Euclidean Distance in Missing Values Imputation on Gene Expression Data

Metode Imputasi Sequential Biclustering Berbasis Shifting-and-Scaling Similarity dan Mean Squared Residue (SSSim-MSR) pada Data Ekspresi Gen Dua Dimensi = Sequential Biclustering Imputation Method Based on Shifting-and-Scaling Similarity and Mean Squared Residue on Two-Dimensional Gene Expression Data

Implementasi Metode Imputasi Ganda Dynamically Ordered Attribute Trees (DOAT) untuk Estimasi Missing Values pada Data Kategorik = Implementation of Dynamically-Ordered Attribute Tree (DOAT) Multiple Imputation Method to Estimate Missing Values in Categorical Data

Implementasi Metode Imputasi Ganda Dynamically Ordered Attribute Trees (DOAT) untuk Estimasi Missing Values pada Data Kategorik = Implementation of Dynamically-Ordered Attribute Tree (DOAT) Multiple Imputation Method to Estimate Missing Values in Categorical Data