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@ -594,6 +594,7 @@ class Predict(GNet):
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#
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# In case we are dealing with actual values like diagnosis codes we can perform
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#
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INDEX = np.random.choice(np.arange(len(found)),1)[0]
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INDEX = ratio.index(np.max(ratio))
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df = found[INDEX]
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@ -609,7 +610,9 @@ class Predict(GNet):
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# let's get the missing rows (if any) ...
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#
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ii = df.apply(lambda row: np.sum(row) == 0 ,axis=1)
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if ii.shape[0] == 0 :
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# print ([' **** ',ii.sum()])
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if ii.shape[0] > 0 :
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#
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#@TODO Have this be a configurable variable
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missing = np.repeat(0, np.where(ii==1)[0].size)
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