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Structure Preprocessing
File check
Validation of molecules
Standardization of molecules
Custom Preprocessing
Data Preprocessing
Imputation of missing values
Removing low variance features
Removing high correlation features
Univariate feature selection
Tree-based feature selection
RFE feature selection
Modelling Process
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Feature Calculation
Model Selection
Model Building
Prediction
Model interpretation
Feature importance
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Statistical Analysis
Random training set split
Diverse training set split
| Step 1: Upload your file
Choose your file:
Example
| Step 2: Set parameters
Choose the missing values type
"NaN" - The placeholder for the missing values in your file.
"0" - The placeholder for the missing values in your file.
Choose the strategy
"mean" - replace missing values using the mean along the axis.
"median" - replace missing values using the median along the axis.
"most_frequent" - replace missing using the most frequent value along the axis.
Choose the axis
"0" - impute along columns.
"1" - impute along rows.
E-mail: biomed@csu.edu.cn
