Machine Learning Bricks

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Apply Ordinal Encoder

Function

Encodes categorical columns to Integers. Automatically detects columns if a fitted encoder is provided.
Apply PCA Transform

Function

Projects data using a pre-trained PCA model. Appends PC columns to the dataset. Note: Filter your columns before this brick if specific features are required.
Apply Scaler

Function

Applies a pre-fitted Scikit-Learn Scaler to the dataset.
Apply Target Encoder

Function

Applies a pre-fitted Target Encoder to a specific series or array.
Apply UMAP Transform

Function

Projects new data using a pre-trained UMAP model. Appends UMAP embedding columns to the dataset. Ensure input features match the training data.
Cla. Decision Tree

Function

Train a Decision Tree classification model.
Cla. K Nearest Neighbors

Function

Train a K-Nearest Neighbors (KNN) classification model.
Cla. LightGBM

Function

Train a LightGBM gradient boosting classification model.
Cla. Logistic Regression

Function

Train a logistic regression classification model with hyperparameter optimization and cross-validation support.
Cla. Random Forest

Function

Train a Random Forest classification model with configurable trees, depth, and sampling strategies.
Classification Metrics

Function

Computes standard classification metrics. Supports specific positive labels for binary classification.
Cla. Support Vector Machine

Function

Train a Support Vector Machine (SVM) classification model.