Add docs

Parsimmon/DecisionTree.swift

@@ -61,11 +61,19 @@ public class DecisionTree {
         self.featureNames = featureNames
         self.classificationNames = classificationNames
     }
-
+
+    /**
+        Adds a data point to the decision tree.
+
+        @param datum A data point
+    */
     public func addSample(datum: Datum) {
         self.data.append(datum)
     }
-
+
+    /**
+        Builds the decision tree based on the data it has.
+    */
     public func build() {
         let features = [ Bit.Zero, Bit.One ]
         self.root = self.decisionTree(self.data, remainingFeatures: features, maxDepth: self.maxDepth)

Parsimmon/Lemmatizer.swift

@@ -33,6 +33,13 @@ public struct Lemmatizer: Analyzer {
         self.seed = seed
     }
 
+    /**
+        Returns the lemmatized tokens for the input text using the specified linguistic tagger options.
+
+        @param text Text to lemmatized
+        @param options Linguistic tagger options
+        @return The lemmatized tokens
+    */
     public func lemmatizeWordsInText(text: String, options: NSLinguisticTaggerOptions? = nil) -> [String] {
         return analyze(self, text, options).map { (token, lemma) in lemma }
     }

Parsimmon/NaiveBayesClassifier.swift

@@ -73,20 +73,22 @@ public class NaiveBayesClassifier {
     // MARK: - Training
 
     /**
-     Trains the classifier with text and its category.
-     @param text The text
-     @param category The category of the text
+        Trains the classifier with text and its category.
+
+        @param text The text
+        @param category The category of the text
     */
     public func trainWithText(text: String, category: Category) {
         let tokens = tokenizer.tokenize(text)
         trainWithTokens(tokens, category: category)
     }
 
     /**
-     Trains the classifier with tokenized text and its category.
-     This is useful if you wish to use your own tokenization method.
-     @param tokens The tokenized text
-     @param category The category of the text
+        Trains the classifier with tokenized text and its category.
+        This is useful if you wish to use your own tokenization method.
+
+        @param tokens The tokenized text
+        @param category The category of the text
     */
     public func trainWithTokens(tokens: [Word], category: Category) {
         let words = Set(tokens)
@@ -100,19 +102,21 @@ public class NaiveBayesClassifier {
     // MARK: - Classifying
 
     /**
-     Classifies the given text based on its training data.
-     @param text The text to classify
-     @return The category classification
+        Classifies the given text based on its training data.
+
+        @param text The text to classify
+        @return The category classification
     */
     public func classify(text: String) -> Category? {
         let tokens = tokenizer.tokenize(text)
         return classifyTokens(tokens)
     }
 
     /**
-     Classifies the given tokenized text based on its training data.
-     @param text The tokenized text to classify
-     @return The category classification if one was found, or nil if one wasn’t
+        Classifies the given tokenized text based on its training data.
+
+        @param text The tokenized text to classify
+        @return The category classification if one was found, or nil if one wasn’t
     */
     public func classifyTokens(tokens: [Word]) -> Category? {
         // Compute argmax_cat [log(P(C=cat)) + sum_token(log(P(W=token|C=cat)))]

Parsimmon/Tagger.swift

@@ -33,6 +33,13 @@ public struct Tagger: Analyzer {
         self.seed = seed
     }
 
+    /**
+        Returns the tagged tokens for the input text using the specified linguistic tagger options.
+
+        @param text Text to tag
+        @param options Linguistic tagger options
+        @return The tagged tokens
+    */
     public func tagWordsInText(text: String, options: NSLinguisticTaggerOptions? = nil) -> [TaggedToken] {
         return analyze(self, text, options).map { (token, tag) in
             TaggedToken(token: token, tag: tag)

Parsimmon/Tokenizer.swift

@@ -33,6 +33,13 @@ public struct Tokenizer: Analyzer {
         self.seed = seed
     }
 
+    /**
+        Returns the tokens for the input text using the specified linguistic tagger options.
+        @param text Text to tokenize
+        @param options Linguistic tagger options
+
+        @return The tokens
+    */
     public func tokenize(text: String, options: NSLinguisticTaggerOptions? = nil) -> [String] {
         return analyze(self, text, options).map { (token, tag) in token }
     }