whole_func_string: function Credulous(options) {
      var i
        ;
      if (!this) {
        return new Credulous(options);
      }
  
      options = validateOptions(options);
  
      this.labels = options.labels;
      this.dataLength = options.dataLength;
      // For the label
      this.trainArgumentsLength = this.dataLength + 1;
  
      // TODO: make the data store more modular
      this.dataStore = [];
      setUpDataStore(this.dataStore, this.labels, this.dataLength);
      this.instancesTrained = 0;
    }
func_code_string: function Credulous(options) {
      var i
        ;
      if (!this) {
        return new Credulous(options);
      }
  
      options = validateOptions(options);
  
      this.labels = options.labels;
      this.dataLength = options.dataLength;
      // For the label
      this.trainArgumentsLength = this.dataLength + 1;
  
      // TODO: make the data store more modular
      this.dataStore = [];
      setUpDataStore(this.dataStore, this.labels, this.dataLength);
      this.instancesTrained = 0;
    }
func_documentation_string: Constructor for the Naive Bayes learner.
  It takes a list of strings, which represent the different
  groups of strings to train on, followed by an array of possible
  classes.
  
  @param options: object of options that set up the naive bayes model.
  It *must* have a `label` property that is an array of possible labels to assign
  to things we are classifying.
  It can optionally have a `dataLength` that specifies how many groups of strings
  we are classifying. This is useful if we are classifying things that have several
  separate attributes that we want to compute probabilities for separately. For
  example, when calssifying an email, we might have three separate things to classify
  on: the text of the email, the text of the subject, and the country of origin in
  the sender's address. In this case, we would set `dataLength` to 3, and pass these
  in as three separate arguments to the `train()` method.