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Update kci.rst #232

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4 changes: 2 additions & 2 deletions docs/source/independence_tests_index/kci.rst
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Expand Up @@ -52,7 +52,7 @@ and n_features is the number of features.

+ Either for specifying parameters of KCI, including:

**KernelX/Y/Z (condition_set)**: ['GaussianKernel', 'LinearKernel', 'PolynomialKernel']. (For 'PolynomialKernel', the default degree is 2. Currently, users can change it by setting the 'degree' of 'class PolynomialKernel()'.
**KernelX/Y/Z (condition_set)**: ['Gaussian', 'Linear', 'Polynomial']. (For 'Polynomial', the default degree is 2. Currently, users can change it by setting the 'degree' of 'class PolynomialKernel()'.

**est_width**: set kernel width for Gaussian kernels.
- 'empirical': set kernel width using empirical rules (default).
Expand All @@ -72,4 +72,4 @@ Returns
**p**: the p value.


.. [1] Zhang, K., Peters, J., Janzing, D., & Schölkopf, B. (2011, July). Kernel-based Conditional Independence Test and Application in Causal Discovery. In 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011) (pp. 804-813). AUAI Press.
.. [1] Zhang, K., Peters, J., Janzing, D., & Schölkopf, B. (2011, July). Kernel-based Conditional Independence Test and Application in Causal Discovery. In 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011) (pp. 804-813). AUAI Press.