update models_class1_experiments1 to include embedding and onehot input variations

downloads-generation/models_class1/hyperparameters.yaml

@@ -26,6 +26,7 @@
 # One of "one-hot", "embedding", or "BLOSUM62".
 "peptide_amino_acid_encoding": "BLOSUM62",
 "use_embedding": false,  # maintained for backward compatability
+"embedding_output_dim": 8,  # only used if using embedding
 "kmer_size": 15,
 
 ##########################################

downloads-generation/models_class1_experiments1/GENERATE.sh

@@ -37,9 +37,9 @@ time mhcflurry-class1-train-allele-specific-models \
     --alleles $ALLELES &
 
 # Model variations on qualitative + quantitative
-for mod in 0local_noL1 0local 1local dense16 dense64 noL1 
+for mod in 0local_noL1 0local 2local dense16 dense64 noL1 onehot embedding
 do
-    cp $SCRIPT_DIR/hyperparameters-${mod}.json .
+    cp $SCRIPT_DIR/hyperparameters-${mod}.yaml .
     mkdir models-${mod}
     time mhcflurry-class1-train-allele-specific-models \
         --data "$(mhcflurry-downloads path data_curated)/curated_training_data.csv.bz2" \

downloads-generation/models_class1_experiments1/hyperparameters-embedding.yaml

+[{
+##########################################
+# ENSEMBLE SIZE
+##########################################
+"n_models": 8,
+
+##########################################
+# OPTIMIZATION
+##########################################
+"max_epochs": 500,
+"patience": 10,
+"early_stopping": true,
+"validation_split": 0.2,
+
+##########################################
+# RANDOM NEGATIVE PEPTIDES
+##########################################
+"random_negative_rate": 0.0,
+"random_negative_constant": 25,
+"random_negative_affinity_min": 20000.0,
+"random_negative_affinity_max": 50000.0,
+
+##########################################
+# PEPTIDE REPRESENTATION
+##########################################
+# One of "one-hot", "embedding", or "BLOSUM62".
+"peptide_amino_acid_encoding": "embedding",
+"use_embedding": true,  # maintained for backward compatability
+"embedding_output_dim": 8,  # only used if using embedding
+"kmer_size": 15,
+
+##########################################
+# NEURAL NETWORK ARCHITECTURE
+##########################################
+"locally_connected_layers": [
+    {
+        "filters": 8,
+        "activation": "tanh",
+        "kernel_size": 3
+    }
+],
+"activation": "relu",
+"output_activation": "sigmoid",
+"layer_sizes": [
+    32
+],
+"dense_layer_l1_regularization": 0.001,
+"batch_normalization": false,
+"dropout_probability": 0.0,
+}]

downloads-generation/models_class1_experiments1/hyperparameters-onehot.yaml

+[{
+##########################################
+# ENSEMBLE SIZE
+##########################################
+"n_models": 8,
+
+##########################################
+# OPTIMIZATION
+##########################################
+"max_epochs": 500,
+"patience": 10,
+"early_stopping": true,
+"validation_split": 0.2,
+
+##########################################
+# RANDOM NEGATIVE PEPTIDES
+##########################################
+"random_negative_rate": 0.0,
+"random_negative_constant": 25,
+"random_negative_affinity_min": 20000.0,
+"random_negative_affinity_max": 50000.0,
+
+##########################################
+# PEPTIDE REPRESENTATION
+##########################################
+# One of "one-hot", "embedding", or "BLOSUM62".
+"peptide_amino_acid_encoding": "one-hot",
+"use_embedding": false,  # maintained for backward compatability
+"kmer_size": 15,
+
+##########################################
+# NEURAL NETWORK ARCHITECTURE
+##########################################
+"locally_connected_layers": [
+    {
+        "filters": 8,
+        "activation": "tanh",
+        "kernel_size": 3
+    }
+],
+"activation": "relu",
+"output_activation": "sigmoid",
+"layer_sizes": [
+    32
+],
+"dense_layer_l1_regularization": 0.001,
+"batch_normalization": false,
+"dropout_probability": 0.0,
+}]