API for genpack/maler
A package for building pipelines of Machine Learning models.

Global functions
MODEL Man page
MODEL-class Man page
accuracy_mae Source code
accuracy_medae Source code
accuracy_rmse Source code
add_keras_layer_dense Source code
best_num_clusters Source code
binary_class_bar Source code
binary_class_pie Source code
build_model_from_template Man page Source code
build_model_instance_from_template Source code
cluster.distances Source code
cluster.moments Source code
correlation Man page Source code
createFeatures Source code
createFeatures.logical Source code
createFeatures.multiplicative Source code
createFeatures.supervisor Source code
create_keras_layers Source code
create_transformer Source code
cross_accuracy Source code
cross_f1 Source code
elbow Man page Source code
evaluateFeatures.logical Source code
evaluateFeatures.multiplicative Source code
feature_booster Source code
fit_models Man page
genBinFeatBoost.fit Source code
geo_mape Source code
getFeatureCorrelations Source code
getFeatureValue Source code
getFeatureValue.logical Source code
getFeatureValue.multiplicative Source code
get_feature_lags Source code
group_features Source code
hp_booster Source code
immune Source code
immuneFeatures Source code
int_ordinals Source code
logit_fwd Source code
logit_inv Source code
mae Source code
mape Source code
medae Source code
model_make_unique_transformer_names Man page
model_types Man page
moment Man page
na2median Man page Source code
optSplit.chi Source code
optSplitColumns.f1 Source code
optimSearch1d Source code
outlier Man page Source code
plot_bindensity Man page Source code
predict_models Man page
r_squared Source code
randint Source code
ranker Man page Source code
reduceFeatures Source code
rmse Source code
scorer Man page
scorer_downsampled Man page
spark.binchisq Source code
spark.dte Source code
spark.optSplit.chi Source code
trim_outliers Source code
genpack/maler documentation built on Jan. 27, 2025, 1:23 p.m.