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authorChris Dyer <cdyer@allegro.clab.cs.cmu.edu>2013-02-11 21:14:10 -0500
committerChris Dyer <cdyer@allegro.clab.cs.cmu.edu>2013-02-11 21:14:10 -0500
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tree7535ceae66478e67819b9545565ee16143a8f6e0 /training/crf/baum_welch_example/README.md
parent06d8ec4c0dc2bbf3c8066d3a284a04290ff6a169 (diff)
Baum Welch training for HMMs
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+Here's how to do Baum-Welch training with `cdec`.
+
+## Set the tags you want.
+
+First, set the number of tags you want in tagset.txt (these
+can be any symbols, listed one after another, separated
+by whitespace), e.g.:
+
+ C1 C2 C3 C4
+
+## Extract the parameter feature names
+
+ ../mpi_extract_features -c cdec.ini -t train.txt
+
+If you have compiled with MPI, you can use `mpirun`:
+
+ mpirun -np 8 ../mpi_extract_features -c cdec.ini -t train.txt
+
+## Randomly initialize the weights file
+
+ sort -u features.* | ./random_init.pl > weights.init
+
+## Run training
+
+ ../mpi_baum_welch -c cdec.ini -t train.txt -w weights.init -n 50
+
+Again, if you have compiled with MPI, you can use `mpirun`:
+
+ mpirun -np 8 ../mpi_baum_welch -c cdec.ini -t train.txt -w weights.init -n 50
+
+The `-n` flag indicates how many iterations to run for.
+