Fix list formatting in missing value tutorial in XGBoost4J-Spark
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@ -161,10 +161,10 @@ Strategies to handle missing values (and therefore overcome issues as above):
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In the case that a feature column contains missing values for any reason (could be related to business logic / wrong data ingestion process / etc.), the user should decide on a strategy of how to handle it.
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The choice of approach depends on the value representing 'missing' which fall into four different categories:
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1. 0.
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2. NaN.
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3. Null.
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4. any other value which is not mentioned in (1) / (2) / (3).
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1. 0
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2. NaN
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3. Null
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4. Any other value which is not mentioned in (1) / (2) / (3)
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We introduce the following approaches dealing with missing value and their fitting scenarios:
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