write k mixture model

diff --git a/utils/training/k_mixture_model.h b/utils/training/k_mixture_model.h
new file mode 100644 (file)
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+++ b/utils/training/k_mixture_model.h
@@ -0,0 +1,110 @@
+/* 
+ *  libpinyin
+ *  Library to deal with pinyin.
+ *  
+ *  Copyright (C) 2011 Peng Wu <alexepico@gmail.com>
+ *  
+ *  This program is free software; you can redistribute it and/or modify
+ *  it under the terms of the GNU General Public License as published by
+ *  the Free Software Foundation; either version 2 of the License, or
+ *  (at your option) any later version.
+ * 
+ *  This program is distributed in the hope that it will be useful,
+ *  but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ *  GNU General Public License for more details.
+ *  
+ *  You should have received a copy of the GNU General Public License
+ *  along with this program; if not, write to the Free Software
+ *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+ */
+
+
+#ifndef K_MIXTURE_MODEL
+#define K_MIXTURE_MODEL
+
+#include "novel_types.h"
+
+namespace pinyin{
+
+typedef guint32 corpus_count_t;
+
+/* Note: storage parameters: N, T, n_r.
+ * N: the total number of documents.
+ * T: the total number of instances of the word or phrase.
+ * n_r: the number of documents having exactly <b>r</b> occurrences.
+ *      only n_0, n_1 are used here.
+ */
+
+static inline parameter_t compute_alpha(corpus_count_t N, corpus_count_t n_0){
+    parameter_t alpha = 1 - n_0 / (parameter_t) N;
+    return alpha;
+}
+
+static inline parameter_t compute_gamma(corpus_count_t N,
+                                        corpus_count_t n_0,
+                                        corpus_count_t n_1){
+    parameter_t gamma = 1 - n_1 / (parameter_t) (N - n_0);
+    return gamma;
+}
+
+static inline parameter_t compute_B(corpus_count_t N,
+                                    corpus_count_t T,
+                                    corpus_count_t n_0,
+                                    corpus_count_t n_1){
+    parameter_t B = (T - n_1 ) / (parameter_t) (N - n_0 - n_1);
+    return B;
+}
+
+/* three parameters model */
+static inline parameter_t compute_Pr_G_3(corpus_count_t k,
+                                         parameter_t alpha,
+                                         parameter_t gamma,
+                                         parameter_t B){
+    if ( k == 0 )
+        return 1 - alpha;
+
+    if ( k == 1 )
+        return alpha * (1 - gamma);
+
+    if ( k > 1 ) {
+        return alpha * gamma / (B - 1) * pow((1 - 1 / (B - 1)) , k - 2);
+    }
+
+    assert(false);
+}
+
+static inline parameter_t compute_Pr_G_3_with_count(corpus_count_t k,
+                                                    corpus_count_t N,
+                                                    corpus_count_t T,
+                                                    corpus_count_t n_0,
+                                                    corpus_count_t n_1){
+    parameter_t alpha = compute_alpha(N, n_0);
+    parameter_t gamma = compute_gamma(N, n_0, n_1);
+    parameter_t B = compute_B(N, T, n_0, n_1);
+
+    return compute_Pr_G_3(k, alpha, gamma, B);
+}
+
+/* two parameters model */
+static inline parameter_t compute_Pr_G_2(corpus_count_t k,
+                                         parameter_t alpha,
+                                         parameter_t B){
+    parameter_t gamma = 1 - 1 / (B - 1);
+    return compute_Pr_G_3(k, alpha, gamma, B);
+}
+
+static inline parameter_t compute_Pr_G_2_with_count(corpus_count_t k,
+                                                    corpus_count_t N,
+                                                    corpus_count_t T,
+                                                    corpus_count_t n_0,
+                                                    corpus_count_t n_1){
+    parameter_t alpha = compute_alpha(N, n_0);
+    parameter_t B = compute_B(N, T, n_0, n_1);
+    return compute_Pr_G_2(k, alpha, B);
+}
+
+};
+
+
+#endif