update description

README.md

@@ -91,7 +91,60 @@ The dataset is generated according to the description in [DoubleMLDeep: Estimati
 
 ### Dataset Description & Usage
 
-The dataset contains the following columns:
+The dataset is a semi-synthetic dataset as a benchmark for treatment effect estimation with multimodal confounding. The outcome
+variable `Y` is generated according to a partially linear model
+$$
+Y = \theta_0 D_1 + g_1(X) + \varepsilon
+$$
+with an constant treatment effect of
+$$\theta_0=0.5.$$
+The target variables `sentiment`, `label` and `price` are used to generate credible confounding by affecting both `Y` and `D_1`.
+This confounding is generated to be negative, such that estimates of the treatment effect should generally be smaller than `0.5`.
+
+For a more detailed description on the data generating process, see [DoubleMLDeep: Estimation of Causal Effects with Multimodal Data](https://arxiv.org/abs/2402.01785).
+
+The dataset includes the corresponding  target variables `sentiment`, `label`, `price` and oracle values such as `cond_exp_y`, `l1`, `m1`, `g1`.
+These values are included for convenience for e.g. benchmarking against optimal estimates, but should not be used in the model.
+Further, several tabular features are highly correlated, such that it may be helpful to drop features such as `x`, `y`, `z`.
+
+An example looks as follows:
+
+```
+{'cond_exp_y': 2.367230022801451,
+ 'm1': -2.7978920933712907,
+ 'g1': 4.015536418538365,
+ 'l1': 2.61659037185272,
+ 'Y': 3.091541535115522,
+ 'D_1': -3.2966127914738275,
+ 'carat': 0.5247285289349821,
+ 'depth': 58.7,
+ 'table': 59.0,
+ 'price': 9.7161333532141,
+ 'x': 7.87,
+ 'y': 7.78,
+ 'z': 4.59,
+ 'review': "I really liked this Summerslam due to the look of the arena, the curtains and just the look overall was interesting to me for some reason. Anyways, this could have been one of the best Summerslam's ever if the WWF didn't have Lex Luger in the main event against Yokozuna, now for it's time it was ok to have a huge fat man vs a strong man but I'm glad times have changed. It was a terrible main event just like every match Luger is in is terrible. Other matches on the card were Razor Ramon vs Ted Dibiase, Steiner Brothers vs Heavenly Bodies, Shawn Michaels vs Curt Hening, this was the event where Shawn named his big monster of a body guard Diesel, IRS vs 1-2-3 Kid, Bret Hart first takes on Doink then takes on Jerry Lawler and stuff with the Harts and Lawler was always very interesting, then Ludvig Borga destroyed Marty Jannetty, Undertaker took on Giant Gonzalez in another terrible match, The Smoking Gunns and Tatanka took on Bam Bam Bigelow and the Headshrinkers, and Yokozuna defended the world title against Lex Luger this match was boring and it has a terrible ending. However it deserves 8/10",
+ 'sentiment': 'positive',
+ 'label': 6,
+ 'cut_Good': False,
+ 'cut_Ideal': False,
+ 'cut_Premium': True,
+ 'cut_Very Good': False,
+ 'color_E': False,
+ 'color_F': True,
+ 'color_G': False,
+ 'color_H': False,
+ 'color_I': False,
+ 'color_J': False,
+ 'clarity_IF': False,
+ 'clarity_SI1': False,
+ 'clarity_SI2': False,
+ 'clarity_VS1': False,
+ 'clarity_VS2': True,
+ 'clarity_VVS1': False,
+ 'clarity_VVS2': False,
+ 'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=32x32>}
+```
 
 ### Dataset Sources
 
@@ -174,7 +227,7 @@ The data fields can be devided into several categories:
   - `cond_exp_y` (`float64`): Expected value of `Y` conditional on `D_1`, `sentiment`, `label` and `price`
   - `l1` (`float64`): Expected value of `Y` conditional on `sentiment`, `label` and `price`
   - `m1` (`float64`): Expected value of `D_1` conditional on `sentiment`, `label` and `price`
-  - `g1` (`float64`): Additive component of `Y` based on `sentiment`, `label` and `price`
+  - `g1` (`float64`): Additive component of `Y` based on `sentiment`, `label` and `price` (see Dataset Description)
 
 ## Limitations