Machine Learning Bricks

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Reg. Support Vector Machine

Function

Train a Support Vector Machine (SVM) regression model.
Reg. XGBoost

Function

Train an XGBoost regression model.
ROC Curve

Function

Computes the Receiver Operating Characteristic (ROC) curve. Returns a DataFrame with 'fpr', 'tpr', and 'thresholds'.
ROC Curve

Graph

Display the Receiver Operating Characteristic (ROC) curve with a threshold slider.
Scikit Object Load

Function

Restores a Scikit-learn object from a ZIP archive or directory created by the Save Scikit Object brick.
Scikit Object Save

Function

Saves Scikit-learn objects (encoders, scalers, pipelines) with metadata into a portable archive.
SHAP Cohorts

Function

Automatically detects cohorts in the data and compares feature importance across them.
SHAP Dependence

Function

Visualizes the relationship between a feature value and its SHAP value. supports coloring by a second feature to reveal interactions.
SHAP Explanation

Function

Explains a single prediction (row) using a waterfall plot. Shows how each feature contributed to pushing the model output from the base value to the final prediction.
SHAP Feature Importance

Function

Calculates feature importance using a pre-built SHAP explainer.
SHAP Heatmap

Function

Generates a SHAP heatmap visualizing feature impacts across instances. Supports ordering by similarity or sum of SHAP values.
SHAP Impact Distribution

Function

Visualizes the distribution of feature impacts. Shows how high/low feature values affect predictions.