Migration from v1 to v2

v2 preserves the project goal but changes internals to a composable pipeline.

Architecture changes

v1	v2	Migration
computeHiddenOutput duplicated across models	FeatureMap::transform	Use RandomAdditiveMap, RbfMap, ElmAutoEncoderLayer, or StackedFeatureMap
Some models accepted Backend	Every model accepts Backend	Pass Backend::kCpu or Backend::kGpu explicitly
RBF activation enum	RbfMap feature map	Replace ActivationFunction::kRbf usage with RbfMap
H-OS-ELM fixed random stack	ELM-AE learned stack	Use HierarchicalOsElm with hiddenNodesPerLayer
Hard-coded 1e-8 ridge term	ridgeAlpha	Pass a positive ridgeAlpha
Demo fabricated training data	Bundled dataset and real metrics	Use dataset IO and demo endpoints

API notes

• BatchElm keeps its constructor shape and adds ridgeAlpha.
• OsElm and OsCelm accept RlsOptions.
• OsCelm gains Backend for consistency.
• HierarchicalOsElm now learns ELM-AE layers during initialization.

Code migration example

Before:

feature_elm::BatchElm<float> model(numInputs, hiddenNodes, feature_elm::ActivationFunction::kSigmoid);

After, with explicit backend and ridge alpha:

feature_elm::BatchElm<float> model(
    numInputs,
    hiddenNodes,
    feature_elm::ActivationFunction::kSigmoid,
    feature_elm::Backend::kCpu,
    1e-6f);

Documentation migration

See upgrade baseline and H-OS-ELM migration for regression notes.