minor style changes

docs/usage.rst

@@ -56,7 +56,7 @@ For those columns the following relationships hold:
  - ``y = t*y_1 + (1-t)*y_0``
  - ``y_cf = (1-t)*y_1 + t*y_0`` (*counterfactual* of ``y``)
  - ``y = y_0 if t == 0 else y_1``
- - ``y_0 = mu_0 + e`` and ``y_1 = mu_1 + e`` where e is some random noise or 0
+ - ``y_0 = mu_0 + e`` and ``y_1 = mu_1 + e`` where e (read epsilon) is some random noise or 0
  - ``ite = mu_1 - mu_0``
 
 Besides these columns, there are covariates (also called features) and optionally other columns for managing meta information
@@ -295,17 +295,17 @@ Given the two functions defined above, we can go ahead and write our own simple
 
 Finally, we can compare the results:
 
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
-| pehe_score-mean | pehe_score-median | pehe_score-std | mean_absolute-mean | mean_absolute-median | mean_absolute-std | method | train |
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
-| 5.633659795888926 | 2.623297102872904 | 8.362124759175456 | 0.7324426200135636 | 0.23818504313199096 | 1.4932757697867256 | basic_slearner | True  |
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
-| 5.6259710007216395 | 2.6359926738390502 | 8.21362597153304 | 1.2926681149657069 | 0.39624557185266274 | 2.474603428686128  | basic_slearner | False |
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
-| 5.5923557213070865 | 2.5694717507474367 | 8.248291408843366 | 0.36993887434693706 | 0.2124273147538498 | 0.5243953093767589 | weighted_slearner | True  |
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
-| 5.493401193725203 | 2.589651399901662 | 7.903173959543366 | 0.6556018033505657 | 0.28720143217333827 | 0.94194122373987  | weighted_slearner | False |
-+--------------------+--------------------+-------------------+---------------------+----------------------+--------------------+-------------------+-------+
++-------------------+-------+--------------------+--------------------+-----+--------------------+
+| method   | train | pehe_score-mean   | pehe_score-median | ... | mean_absolute-std  |
++-------------------+-------+--------------------+--------------------+-----+--------------------+
+| basic_slearner | True | 5.633659795888926 | 2.623297102872904 | ... | 1.4932757697867256 |
++-------------------+-------+--------------------+--------------------+-----+--------------------+
+| basic_slearner | False | 5.6259710007216395 | 2.6359926738390502 | ... | 2.474603428686128 |
++-------------------+-------+--------------------+--------------------+-----+--------------------+
+| weighted_slearner | True | 5.5923557213070865 | 2.5694717507474367 | ... | 0.5243953093767589 |
++-------------------+-------+--------------------+--------------------+-----+--------------------+
+| weighted_slearner | False | 5.493401193725203 | 2.589651399901662 | ... | 0.94194122373987 |
++-------------------+-------+--------------------+--------------------+-----+--------------------+
 
 Understanding Scores and Results
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