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Fix formatting of hierarchical precision formula

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@@ -34,7 +34,7 @@ The measure accounts for the hierarchical structure of the ISCO-08 classificatio
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  The features described are accomplished by pairing hierarchical variants of precision ($hP$) and recall ($hR$) to form a hierarchical F1 ($hF_β$) score where each sample belongs not only to its class (e.g., a unit group level code), but also to all ancestors of the class in a hierarchical graph (i.e., the minor, sub-major, and major group level codes).
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- Hierarchical precision can be computed with: $hP=\\frac{| \\v{C}_i ∩ \\v{C}^′_i|} {|\\v{C}^′_i|}=\\frac{1}{2}$
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  Hierarchical recall can be computed with:
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  `$hR = \frac{| \v{C}_i ∩ \v{C}^′_i|} {|\v{C}_i |} = \frac{1}{2}$`
 
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  The features described are accomplished by pairing hierarchical variants of precision ($hP$) and recall ($hR$) to form a hierarchical F1 ($hF_β$) score where each sample belongs not only to its class (e.g., a unit group level code), but also to all ancestors of the class in a hierarchical graph (i.e., the minor, sub-major, and major group level codes).
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+ Hierarchical precision can be computed with: `$hP=\\frac{| \\v{C}_i ∩ \\v{C}^′_i|} {|\\v{C}^′_i|}=\\frac{1}{2}$`
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  Hierarchical recall can be computed with:
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  `$hR = \frac{| \v{C}_i ∩ \v{C}^′_i|} {|\v{C}_i |} = \frac{1}{2}$`