title: mlr_measures_classif.costs with predict_type = "prob"
body: <p>The cost-sensitive measure <code>mlr_measures_classif.costs</code> requires a <code>'response'</code> predict type.</p>
  
  <pre><code>msr("classif.costs")
  #&lt;MeasureClassifCosts:classif.costs&gt;
  #* Packages: -
  #* Range: [-Inf, Inf]
  #* Minimize: TRUE
  #* Properties: requires_task
  #* Predict type: response
  </code></pre>
  
  <p>This measure seems to be working even when a learner's <code>predict_type</code> is set to <code>'prob'</code>:</p>
  
  <pre><code># get a cost sensitive task
  task = tsk("german_credit")
  
  # cost matrix as given on the UCI page of the german credit data set
  # https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)
  costs = matrix(c(0, 5, 1, 0), nrow = 2)
  dimnames(costs) = list(truth = task$class_names, predicted = task$class_names)
  print(costs)
  
  # mlr3 needs truth in columns, predictions in rows
  costs = t(costs)
  
  # create measure which calculates the absolute costs
  m = msr("classif.costs", id = "german_credit_costs", costs = costs, normalize = FALSE)
  
  # fit models and calculate costs
  learner = lrn("classif.rpart", predict_type = "prob")
  rr = resample(task, learner, rsmp("cv", folds = 3))
  rr$aggregate(m)
  
  #german_credit_costs 
  #               341
  </code></pre>
  
  <p>Why is it working with <code>predict_type</code> is set to <code>'prob'</code>? Is this a bug or does the measure internally convert probabilities into classes? I guess the threshold for predicting a class as positive or negative is internally set to 0.5? Can one change this threshold?</p>