tech.ml.dataset.pipeline.pipeline-operators — techascent/tech.ml.dataset 2.15

*pipeline-context* clj

*pipeline-env* clj

*pipeline-training?* clj

->datatype clj

assoc-metadata clj

def-multiple-column-etl-operator clj macro

(def-multiple-column-etl-operator op-symbol _docstring op-context-code op-code)

def-single-column-etl-operator clj macro

(def-single-column-etl-operator op-symbol _docstring op-context-code op-code)

default-etl-context-columns clj

(default-etl-context-columns op dataset column-name-seq op-args)

Default implementation of build-etl-context-columns

default-perform-etl-columns clj

(default-perform-etl-columns op dataset column-name-seq op-args context)

filter clj

impute-missing clj

inline-perform-operator clj

(inline-perform-operator etl-op dataset column-filter op-args)

m= clj

one-hot clj

pca clj

pif clj

(pif dataset bool-expr pipe-when-true pipe-when-false)

pipeline-inference-context clj macro

(pipeline-inference-context train-context & body)

pipeline-train-context clj macro

(pipeline-train-context & body)

pwhen clj

(pwhen dataset bool-expr pipe-when-true)

range-scaler clj

read-var clj

(read-var varname)

remove-columns clj

replace clj

replace-missing clj

std-scaler clj

store-variables clj

(store-variables dataset varmap-fn)

string->number clj

training? clj

(training?)

update-column clj

without-recording clj macro

(without-recording & body)