diff --git a/docs/source/api_ref/datasets.rst b/docs/source/api_ref/datasets.rst index 3424b35cb..2e734de1d 100644 --- a/docs/source/api_ref/datasets.rst +++ b/docs/source/api_ref/datasets.rst @@ -6,52 +6,52 @@ Built-in Datasets :members: Amazon Clothing ------------------------------------------------ +--------------- .. automodule:: cornac.datasets.amazon_clothing :members: Amazon Digital Music ------------------------------------------------ +-------------------- .. automodule:: cornac.datasets.amazon_digital_music :members: Amazon Office ---------------------------------------------- +------------- .. automodule:: cornac.datasets.amazon_office :members: Amazon Toys and Games ---------------------------------------------- +--------------------- .. automodule:: cornac.datasets.amazon_toy :members: CiteULike ------------------------------------------ +--------- .. automodule:: cornac.datasets.citeulike :members: Epinions ------------------------------------------ +-------- .. automodule:: cornac.datasets.epinions :members: FilmTrust ---------------------------------------------- +--------- .. automodule:: cornac.datasets.filmtrust :members: MovieLens ------------------------------------------ +--------- .. automodule:: cornac.datasets.movielens :members: Netflix ---------------------------------------- +------- .. automodule:: cornac.datasets.netflix :members: Tradesy ---------------------------------------- +------- .. automodule:: cornac.datasets.tradesy :members: diff --git a/docs/source/api_ref/eval_methods.rst b/docs/source/api_ref/eval_methods.rst index d2da18167..79e6ee79f 100644 --- a/docs/source/api_ref/eval_methods.rst +++ b/docs/source/api_ref/eval_methods.rst @@ -1,29 +1,29 @@ Evaluation Methods -====================== +================== .. automodule:: cornac.eval_methods Base Method ------------------------------------------------ +----------- .. automodule:: cornac.eval_methods.base_method :members: Cross Validation ----------------------------------------------------- +---------------- .. automodule:: cornac.eval_methods.cross_validation :members: Propensity Stratified Evaluation --------------------------------------------------------------------- +-------------------------------- .. automodule:: cornac.eval_methods.propensity_stratified_evaluation :members: Ratio Split ------------------------------------------------ +----------- .. automodule:: cornac.eval_methods.ratio_split :members: Stratified Split ----------------------------------------------------- +---------------- .. automodule:: cornac.eval_methods.stratified_split - :members: \ No newline at end of file + :members: diff --git a/docs/source/api_ref/index.rst b/docs/source/api_ref/index.rst index 390eb1661..10745172a 100644 --- a/docs/source/api_ref/index.rst +++ b/docs/source/api_ref/index.rst @@ -1,7 +1,8 @@ API Reference ============= -Welcome to the API Reference. +Welcome to the API Reference. This section contains the documentation of the +functions and classes of the ``cornac`` package. .. toctree:: :maxdepth: 2 @@ -13,4 +14,4 @@ Welcome to the API Reference. eval_methods experiment datasets - hyperopt \ No newline at end of file + hyperopt diff --git a/docs/source/api_ref/metrics.rst b/docs/source/api_ref/metrics.rst index b9bba4907..cfb5969ca 100644 --- a/docs/source/api_ref/metrics.rst +++ b/docs/source/api_ref/metrics.rst @@ -8,7 +8,7 @@ Rating ++++++ Mean Absolute Error (MAE) ----------------------------- +------------------------- .. autoclass:: MAE Mean Squared Error (MSE) @@ -16,7 +16,7 @@ Mean Squared Error (MSE) .. autoclass:: MSE Root Mean Squared Error (RMSE) --------------------------------- +------------------------------ .. autoclass:: RMSE +++++++ @@ -28,7 +28,7 @@ Area Under the Curve (AUC) .. autoclass:: AUC Fmeasure (F1) -------------------- +------------- .. autoclass:: FMeasure Mean Average Precision (MAP) @@ -36,7 +36,7 @@ Mean Average Precision (MAP) .. autoclass:: MAP Mean Reciprocal Rank (MRR) -------------------------------------------- +-------------------------- .. autoclass:: MRR Normalized Cumulative Reciprocal Rank (NCRR) @@ -44,13 +44,13 @@ Normalized Cumulative Reciprocal Rank (NCRR) .. autoclass:: NCRR Normalized Discount Cumulative Gain (NDCG) -------------------------------------------- +------------------------------------------ .. autoclass:: NDCG Precision -------------------- +--------- .. autoclass:: Precision Recall -------------------- -.. autoclass:: Recall \ No newline at end of file +------ +.. autoclass:: Recall diff --git a/docs/source/api_ref/models.rst b/docs/source/api_ref/models.rst index 08d2061a9..63bb63847 100644 --- a/docs/source/api_ref/models.rst +++ b/docs/source/api_ref/models.rst @@ -1,17 +1,18 @@ Models -=========== +====== +Below are the models that are currently supported in Cornac. .. automodule:: cornac.models :members: Recommender (Generic Class) ------------------------------------------ +--------------------------- .. automodule:: cornac.models.recommender :members: Bilateral VAE for Collaborative Filtering (BiVAECF) ----------------------------------------------------- +--------------------------------------------------- .. automodule:: cornac.models.bivaecf.recom_bivaecf :members: @@ -24,147 +25,147 @@ Explainable Recommendation with Comparative Constraints on Product Aspects (Comp ------------------------------------------------------------------------------------- .. automodule:: cornac.models.comparer.recom_comparer_sub :members: - + .. automodule:: cornac.models.comparer.recom_comparer_obj :members: - + Adversarial Training Towards Robust Multimedia Recommender System (AMR) ----------------------------------------------------- +----------------------------------------------------------------------- .. automodule:: cornac.models.amr.recom_amr :members: Embarrassingly Shallow Autoencoders for Sparse Data (EASEá´¿) --------------------------------------------------- +----------------------------------------------------------- .. automodule:: cornac.models.ease.recom_ease :members: Collaborative Context Poisson Factorization (C2PF) ----------------------------------------------------- +-------------------------------------------------- .. automodule:: cornac.models.c2pf.recom_c2pf :members: Graph Convolutional Matrix Completion (GCMC) ----------------------------------------------------- +-------------------------------------------- .. automodule:: cornac.models.gcmc.recom_gcmc :members: Multi-Task Explainable Recommendation (MTER) ----------------------------------------------------- +-------------------------------------------- .. automodule:: cornac.models.mter.recom_mter :members: Hybrid neural recommendation with joint deep representation learning of ratings and reviews (HRDR) ---------------------------------------------------------------------------- +-------------------------------------------------------------------------------------------------- .. automodule:: cornac.models.hrdr.recom_hrdr :members: Simplifying and Powering Graph Convolution Network for Recommendation (LightGCN) ----------------------------------------------------- +-------------------------------------------------------------------------------- .. automodule:: cornac.models.lightgcn.recom_lightgcn :members: Neural Attention Rating Regression with Review-level Explanations (NARRE) ---------------------------------------------------------------------------- +------------------------------------------------------------------------- .. automodule:: cornac.models.narre.recom_narre :members: Neural Graph Collaborative Filtering (NGCF) ----------------------------------------------------- +------------------------------------------- .. automodule:: cornac.models.ngcf.recom_ngcf :members: Probabilistic Collaborative Representation Learning (PCRL) ------------------------------------------------------------- +---------------------------------------------------------- .. automodule:: cornac.models.pcrl.recom_pcrl :members: VAE for Collaborative Filtering (VAECF) ----------------------------------------------------- +--------------------------------------- .. automodule:: cornac.models.vaecf.recom_vaecf :members: Conditional VAE for Collaborative Filtering (CVAECF) -------------------------------------------------------- +---------------------------------------------------- .. automodule:: cornac.models.cvaecf.recom_cvaecf :members: Collaborative Variational Autoencoder (CVAE) ----------------------------------------------- +-------------------------------------------- .. automodule:: cornac.models.cvae.recom_cvae :members: Generalized Matrix Factorization (GMF) ------------------------------------------ +-------------------------------------- .. automodule:: cornac.models.ncf.recom_gmf :members: Indexable Bayesian Personalized Ranking (IBPR) ------------------------------------------------ +---------------------------------------------- .. automodule:: cornac.models.ibpr.recom_ibpr :members: Matrix Co-Factorization (MCF) ------------------------------------------ +----------------------------- .. automodule:: cornac.models.mcf.recom_mcf :members: Multi-Layer Perceptron (MLP) ------------------------------------------ +---------------------------- .. automodule:: cornac.models.ncf.recom_mlp :members: Neural Matrix Factorization (NeuMF/NCF) ----------------------------------------------- +--------------------------------------- .. automodule:: cornac.models.ncf.recom_neumf :members: Online Indexable Bayesian Personalized Ranking (OIBPR) ------------------------------------------------------------ +------------------------------------------------------ .. automodule:: cornac.models.online_ibpr.recom_online_ibpr :members: Visual Matrix Factorization (VMF) ------------------------------------------ +--------------------------------- .. automodule:: cornac.models.vmf.recom_vmf :members: Collaborative Deep Ranking (CDR) ---------------------------------------- +-------------------------------- .. automodule:: cornac.models.cdr.recom_cdr :members: Collaborative Ordinal Embedding (COE) --------------------------------------------- +------------------------------------- .. automodule:: cornac.models.coe.recom_coe :members: Convolutional Matrix Factorization (ConvMF) --------------------------------------------------- +------------------------------------------- .. automodule:: cornac.models.conv_mf.recom_convmf :members: Spherical k-means (Skmeans) ----------------------------- +--------------------------- .. automodule:: cornac.models.skm.recom_skmeans :members: Visual Bayesian Personalized Ranking (VBPR) ------------------------------------------------ +------------------------------------------- .. automodule:: cornac.models.vbpr.recom_vbpr :members: Collaborative Deep Learning (CDL) ---------------------------------------------- +--------------------------------- .. automodule:: cornac.models.cdl.recom_cdl :members: Hierarchical Poisson Factorization (HPF) --------------------------------------------- +---------------------------------------- .. automodule:: cornac.models.hpf.recom_hpf :members: TriRank: Review-aware Explainable Recommendation by Modeling Aspects (TriRank) --------------------------------------------- +------------------------------------------------------------------------------ .. automodule:: cornac.models.trirank.recom_trirank :members: @@ -174,96 +175,96 @@ Explicit Factor Model (EFM) :members: Social Bayesian Personalized Ranking (SBPR) --------------------------------------------------- +------------------------------------------- .. autoclass:: cornac.models.sbpr.recom_sbpr.SBPR :members: Hidden Factors and Hidden Topics (HFT) ---------------------------------------------- +-------------------------------------- .. automodule:: cornac.models.hft.recom_hft :members: Weighted Bayesian Personalized Ranking (WBPR) ------------------------------------------------- +--------------------------------------------- .. autoclass:: cornac.models.bpr.recom_wbpr.WBPR :members: Collaborative Topic Regression (CTR) -------------------------------------------- +------------------------------------ .. automodule:: cornac.models.ctr.recom_ctr :members: Baseline Only ---------------------------------------------------- +------------- .. autoclass:: cornac.models.baseline_only.recom_bo :members: Bayesian Personalized Ranking (BPR) ----------------------------------------------- +----------------------------------- .. autoclass:: cornac.models.bpr.recom_bpr.BPR :members: Factorization Machines (FM) -------------------------------------------- +--------------------------- .. autoclass:: cornac.models.fm.recom_fm.FM :members Global Average (GlobalAvg) ---------------------------------------------------------- +-------------------------- .. automodule:: cornac.models.global_avg.recom_global_avg :members: Item K-Nearest-Neighbors (ItemKNN) --------------------------------------------------- +---------------------------------- .. autoclass:: cornac.models.knn.recom_knn.ItemKNN :members: Learn to Rank user Preferences based on Phrase-level sentiment analysis across Multiple categories (LRPPM) --------------------------------------------------- +---------------------------------------------------------------------------------------------------------- .. autoclass:: cornac.models.lrppm.recom_lrppm.LRPPM :members: Matrix Factorization (MF) ------------------------------------------- +------------------------- .. automodule:: cornac.models.mf.recom_mf :members: Maximum Margin Matrix Factorization (MMMF) ---------------------------------------------- +------------------------------------------ .. automodule:: cornac.models.mmmf.recom_mmmf :members: Most Popular (MostPop) ------------------------------------------------------ +---------------------- .. automodule:: cornac.models.most_pop.recom_most_pop :members: Non-negative Matrix Factorization (NMF) --------------------------------------------- +--------------------------------------- .. automodule:: cornac.models.nmf.recom_nmf :members: Probabilitic Matrix Factorization (PMF) --------------------------------------------- +--------------------------------------- .. automodule:: cornac.models.pmf.recom_pmf :members: Singular Value Decomposition (SVD) -------------------------------------------- +---------------------------------- .. automodule:: cornac.models.svd.recom_svd :members: Social Recommendation using PMF (SoRec) ------------------------------------------------- +--------------------------------------- .. automodule:: cornac.models.sorec.recom_sorec :members: User K-Nearest-Neighbors (UserKNN) --------------------------------------------------- +---------------------------------- .. autoclass:: cornac.models.knn.recom_knn.UserKNN :members: Weighted Matrix Factorization (WMF) --------------------------------------------------- +----------------------------------- .. automodule:: cornac.models.wmf.recom_wmf :members: \ No newline at end of file