Please make sure you identify the target or Sample ID columns to allow the imputation process run smoothly.
If you have a Target or Sample ID column, click on the corresponding button from the box on the left side.
Loaded Data Checker
Section 2: Basic Statistics Plot
Percentage of Missing Rate
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Correlation Pattern Among Features
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Section 3: Visualization of Missingness Pattern
Image plot of the missingness
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Dendrogram for the missingness
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Confirm to proceed to Imputation
Section 4: Imputation of the Data
Select an Imputation Method
Download Imputed Data
K-Nearest Neighbors
Batch Size (2Value):
Hint Rate
Alpha
Iterations
Minimum Samples Split
Minimum Samples Leaf
Minimum Weight Fraction Leaf
Maximum Iterations
Number of Estimators
Minimum Impurity Decerase
Minimum Child Weight
Feature Fraction
Learning Rate
Minimum Data In Leaf
Bagging Fraction
Regulator Alpha
Regulator Lambda
Number of Estimators
Maximum Iterations
Maximum Iterations
# of Estimators
Learning Rate
Seed
Subsample
Maximum Depth
Regulator Alpha
Regulator Lambda
Column Samples by Tree
Minimum Child Weight
Imputed Data
Select Dataset:
Section 5: Imputation Evaluation Plots
Imputation Accuracy
Section 6: Visualization after Imputation
Elbow Method to Check Optimal Number of Clusters
Visualization of Combination of Dimensional Reduction Algorithms and K-means Clustering
Select Plot Parameters:
Confirm to proceed to Column Specific Analysis
Minimum Child Weight
Feature Fraction
Learning Rate
Minimum Data In Leaf
Bagging Fraction
Maximum Iterations
Regulator Lambda
Choose X iportant Features to Show
Regulator Alpha
Visualization of The Important Features
Select Dataset:
Please select the filters from the selection panels above the plot
Minimum Child Weight
Feature Fraction
Learning Rate
Minimum Data In Leaf
Bagging Fraction
Maximum Iterations
Regulator Lambda
Regulator Alpha
Visualization of the Phenotype Prediction Via Different Imputation Method