Changeset 1176

Timestamp:

Feb 27, 2008, 5:58:15 PM (14 years ago)

Author:

Markus Ringnér

Message:

Working on #75

File:

• trunk/yat/classifier/SupervisedClassifier.h (modified) (3 diffs)

trunk/yat/classifier/SupervisedClassifier.h

@@ -43 +43 @@
 
   ///
-  /// @brief Interface class for supervised classifiers
+  /// @brief Interface class for supervised classifiers that use data
+  /// in a matrix format with data points as columns and each row
+  /// corresponding to a variable for the data points. Supervised
+  /// classifiers that do not use data in this format include
+  /// kernel-based classifiers such as SVM.
   ///
-
   class SupervisedClassifier
   {
@@ -63 +66 @@
 
     ///
-    /// An interface for making new classifier objects. This function
-    /// allows for specification at run-time of which classifier to
-    /// instatiate (see 'Prototype' in Design Patterns).
+    /// An interface for making new %classifier objects. This function
+    /// allows for specification at run-time of which %classifier type
+    /// to instatiate (see 'Prototype' in Design Patterns). Derived
+    /// classes should implement this function with DerivedClass* as
+    /// the return type and not SupervisedClassifier*, and a
+    /// dynamically allocated %classifier should be returned. The
+    /// implementation of this function should correspond to a copy
+    /// constructor with the exception that the returned %classifier
+    /// is not trained.
     ///
-    /// @note Returns a dynamically allocated SupervisedClassifier, which has
+    /// @note Returns a dynamically allocated %classifier, which has
     /// to be deleted by the caller to avoid memory leaks.
     ///
@@ -87 +96 @@
 
     ///
-    /// Train the classifier.
+    /// Train the %classifier using unweighted training data and
+    /// targets. The training data \a data should have one column per
+    /// training sample and one row for each variable measured for the
+    /// training samples. The size of \a target should be the number
+    /// of samples in \a data and \a target should contain the class
+    /// for each sample ordered in the same order as columns in \a data.
     ///
-    virtual void train(const MatrixLookup&, const Target&)=0;
+    virtual void train(const MatrixLookup& data, const Target& targets)=0;
 
     ///
-    /// Train the classifier.
+    /// Train the %classifier using weighted training data and
+    /// targets. Both \a data and \a targets should follow the
+    /// description for train(const MatrixLookup& data, const Target& targets)
     ///
-    virtual void train(const MatrixLookupWeighted&, const Target&)=0;
+    virtual void train(const MatrixLookupWeighted& data, const Target& targets)=0;
 
   };