RcppML/_pkgdown.yml at main · zdebruine/RcppML · GitHub

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url: https://zdebruine.github.io/RcppML/
template:
  bootstrap: 5

articles:
  - title: "Getting Started"
    navbar: ~
    contents:
      - getting-started

  - title: "Core Techniques"
    contents:
      - nmf-fundamentals
      - svd-pca
      - cross-validation
      - distributions
      - regularization

  - title: "Advanced Methods"
    contents:
      - clustering
      - factor-graphs
      - guided-nmf

  - title: "Infrastructure"
    contents:
      - streampress
      - gpu-acceleration

reference:
  - title: "Non-negative Matrix Factorization"
    desc: "Core NMF functions and model class"
    contents:
      - nmf
      - nmf-class
      - "`subset,nmf-method`"
      - "`summary,nmf-method`"
      - "`biplot,nmf-method`"
      - nnls
      - compute_target
      - refine

  - title: "Singular Value Decomposition"
    desc: "SVD and PCA functions"
    contents:
      - svd
      - svd-class
      - pca

  - title: "Model Evaluation & Diagnostics"
    desc: "Functions for evaluating and comparing NMF models"
    contents:
      - assess
      - as.data.frame.nmf_assessment
      - print.nmf_assessment
      - evaluate
      - sparsity
      - align
      - compare_nmf
      - cosine

  - title: "Distribution Selection"
    desc: "Automatic distribution and zero-inflation diagnostics"
    contents:
      - auto_nmf_distribution
      - score_test_distribution
      - diagnose_zero_inflation
      - diagnose_dispersion

  - title: "Visualization"
    desc: "Plotting functions for NMF results"
    contents:
      - plot.nmf
      - plot.nmfCrossValidate

  - title: "Consensus Clustering"
    desc: "Multi-replicate consensus NMF"
    contents:
      - consensus_nmf
      - plot.consensus_nmf
      - summary.consensus_nmf

  - title: "Clustering"
    desc: "NMF-based clustering algorithms"
    contents:
      - bipartition
      - dclust
      - plot.dclust
      - bipartiteMatch

  - title: "Composable Factorization Graphs"
    desc: "Build complex factorization pipelines with factor_net"
    contents:
      - factor_net
      - factor_input
      - factor_config
      - nmf_layer
      - svd_layer
      - factor_shared
      - factor_concat
      - factor_add
      - factor_condition
      - fit
      - W
      - cross_validate_graph
      - predict.factor_net_result
      - training_logger
      - export_log
      - plot.training_logger
      - as.data.frame.training_logger
      - classify_embedding
      - classify_logistic
      - classify_rf
      - "`$.factor_net_result`"
      - print.factor_net
      - print.factor_net_cv
      - print.factor_net_result
      - print.fn_factor_config
      - print.fn_global_config
      - print.fn_node
      - print.fn_classifier_eval
      - summary.factor_net_result
      - summary.fn_classifier_eval
      - print.training_logger

  - title: "Simulation"
    desc: "Functions for generating synthetic data"
    contents:
      - simulateNMF
      - simulateSwimmer

  - title: "StreamPress I/O"
    desc: "Streaming sparse matrix format (.spz)"
    contents:
      - starts_with("st_")
      - streampress

  - title: "GPU Support"
    desc: "GPU acceleration functions"
    contents:
      - gpu_available
      - gpu_info
      - gpu-backend
      - gpu_sparse_matrix-methods

  - title: "Datasets"
    desc: "Built-in datasets for examples and benchmarks"
    contents:
      - aml
      - digits
      - golub
      - hawaiibirds
      - movielens
      - olivetti
      - pbmc3k

  - title: "Package"
    contents:
      - RcppML-package