scicloj.metamorph.ml.preprocessing — org.scicloj/metamorph.ml 1.5.1

Feature scaling and normalization transformers for metamorph pipelines.

This namespace provides metamorph-compatible transformers for standardizing and normalizing numeric features. These preprocessing steps are essential for many machine learning algorithms to perform well.

Available Transformers:

• std-scale: Standardization (z-score normalization)
• min-max-scale: Min-max scaling to a specified range

StandardScaling (std-scale): Centers each numeric column (subtract mean) and/or scales by standard deviation, producing zero-mean unit-variance data. Useful for:

• Algorithms sensitive to feature magnitude (SVMs, neural networks, KNN)
• Distance-based models Options:
• :mean? (default true): Center by subtracting column mean
• :stddev? (default true): Scale by standard deviation

Min-Max Scaling (min-max-scale): Rescales each numeric column to a specified range (default [-0.5, 0.5]). Options:

• :min (default -0.5): Target minimum value
• :max (default 0.5): Target maximum value

Metamorph Integration: Both transformers follow the metamorph pipeline pattern:

• :fit mode: Learn scaling parameters from training data
• :transform mode: Apply learned parameters to new data
• Stores transformation parameters in context under their assigned :metamorph/id

Example Usage (in metamorph pipeline): (preprocessing/std-scale [:age :income] {:mean? true :stddev? true}))

min-max-scale clj

(min-max-scale columns-selector
               {:keys [min max] :or {min -0.5 max 0.5} :as options})

Metamorph transfomer, which scales the column data into a given range.

columns-selector tablecloth columns-selector to choose columns to work on meta-field tablecloth meta-field working with columns-selector

options Options for scaler, can take: min Minimal value to scale to (default -0.5) max Maximum value to scale to (default 0.5)

metamorph	.
Behaviour in mode :fit	Scales the dataset at key :metamorph/data and stores the trained model in ctx under key at :metamorph/id
Behaviour in mode :transform	Reads trained min-max-scale model from ctx and applies it to data in :metamorph/data
Reads keys from ctx	In mode :transform : Reads trained model to use for from key in :metamorph/id.
Writes keys to ctx	In mode :fit : Stores trained model in key $id

std-scale clj

(std-scale columns-selector options)

(std-scale columns-selector
           meta-field
           {:keys [mean? stddev?] :or {mean? true stddev? true} :as options})

Metamorph transfomer, which centers and scales the dataset per column.

columns-selector tablecloth columns-selector to choose columns to work on meta-field tablecloth meta-field working with columns-selector

options are the options for the scaler and can take: mean? If true (default), the data gets shifted by the column means, so 0 centered stddev? If true (default), the data gets scaled by the standard deviation of the column

metamorph	.
Behaviour in mode :fit	Centers and scales the dataset at key :metamorph/data and stores the trained model in ctx under key at :metamorph/id
Behaviour in mode :transform	Reads trained std-scale model from ctx and applies it to data in :metamorph/data
Reads keys from ctx	In mode :transform : Reads trained model to use for from key in :metamorph/id.
Writes keys to ctx	In mode :fit : Stores trained model in key $id