SVDclass-class

SVDclass

show,SVDclass-method

Container for the model learned using any matrix factorization algorithm.

Provides implementations of several popular recommendation systems. They can process standard recommendation datasets (user/item matrix) as input and generate rating predictions and recommendation lists.  Standard algorithm implementations included in this package are: Global/Item/User-Average baselines, Item-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology for recommender systems using measures such as MAE, RMSE, Precision, Recall, AUC, NDCG, RankScore and coverage measures. The package is intended for rapid prototyping of recommendation algorithms and education purposes.

Ludovik oba

rrecsys

Environment for Assessing Recommender Systems

Ludovik <c3><87>oba

Markus Zanker

SVDclass function

<dl class="dl-horizontal">
 <dt><code>alg</code>:</dt><dd>The algorithm denominator, of class <code>"character"</code>.</dd>
 <dt><code>data</code>:</dt><dd>the dataset used for training the model, class <code>"matrix"</code>.</dd>
 <dt><code>factors</code>:</dt><dd>user(U) and items(V) factors, class <code>"list"</code>.</dd>
 <dt><code>parameters</code>:</dt><dd>the parameters(such as number of factors <code>k</code>, learning rate <code>lambda</code>, regularization term <code>gamma</code> and number of iterations until <code>convergence</code>) used in the model, class <code>"list"</code>.</dd>
 </dl>

Slots

<dl class="dl-horizontal">
 <dt><code>show</code></dt><dd>signature(object = "SVDclass")</dd>
 </dl>

Methods

SVD model. — SVDclass

<dl class='dl-horizontal'>
 <dt><code>alg</code>:</dt><dd>The algorithm denominator, of class <code>"character"</code>.</dd>
 <dt><code>data</code>:</dt><dd>the dataset used for training the model, class <code>"matrix"</code>.</dd>
 <dt><code>factors</code>:</dt><dd>user(U) and items(V) factors, class <code>"list"</code>.</dd>
 <dt><code>parameters</code>:</dt><dd>the parameters(such as number of factors <code>k</code>, learning rate <code>lambda</code>, regularization term <code>gamma</code> and number of iterations until <code>convergence</code>) used in the model, class <code>"list"</code>.</dd>
 </dl>

<dl class='dl-horizontal'>
 <dt><code>show</code></dt><dd>signature(object = "SVDclass")</dd>
 </dl>

SVDclass: SVD model.

Description

Arguments

Slots

Methods

See Also