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@@ -1,13 +1,28 @@
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-train {
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- max_train = 1k; # Number of trains per epoch
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- max_usages = 50; # Number of learn iterations while ANN data is valid
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- spam_score = 12; # Score to learn spam
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- ham_score = -7; # Score to learn ham
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- learning_rate = 0.01; # Rate of learning (Torch only)
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- max_iterations = 25; # Maximum iterations of learning (Torch only)
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+rules {
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+ "LONG" {
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+ train {
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+ max_trains = 200;
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+ max_usages = 20;
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+ max_iterations = 25;
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+ learning_rate = 0.01,
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+ spam_score = 12;
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+ ham_score = -7;
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+ }
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+ symbol_spam = "NEURAL_SPAM_LONG";
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+ symbol_ham = "NEURAL_HAM_LONG";
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+ ann_expire = 45d;
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+ }
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+ "SHORT" {
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+ train {
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+ max_trains = 100;
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+ max_usages = 10;
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+ max_iterations = 15;
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+ learning_rate = 0.01,
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+ spam_score = 9;
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+ ham_score = -3;
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+ }
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+ symbol_spam = "NEURAL_SPAM_SHORT";
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+ symbol_ham = "NEURAL_HAM_SHORT";
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+ ann_expire = 7d;
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+ }
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}
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-ann_expire = 80d;
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-timeout = 20; # Increase redis timeout
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-enabled = false;
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-use_settings = false; # If enabled, then settings-id is used to dispatch networks
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-
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