title: about lightFM,How to embed the feature matrix and recommend new projects to user
body: <p>my goal is to fit a model that suit my personal DATA,and I have processed the data and made it three files :
  interaction matrix(394*2188);    item feature matrix(5241*5241);    user feature matrix(1043*1043); I have converted all of them into sparse matrix, and my both feature matrixs contain more content than interactions. when I fit the model by these data and make prediction,there are my codes and errors:
  codes:</p>
  
  <pre><code>model = LightFM(loss='warp')
  model.fit(data,item_features=items,user_features=users,epochs=30, num_threads=2)
  evaluation.auc_score(model,data)
  </code></pre>
  
  <p>errors:
      <strong>raise ValueError('Incorrect number of features in item_features')
  ValueError: Incorrect number of features in item_features</strong></p>
  
  <ol>
  <li>how can I convert data that the interaction matrix’s users and items are less than features matrix</li>
  <li>how can I recommend new and old items to all users(including the new)</li>
  </ol>