Remove documentations for chocolate suggestion service

Signed-off-by: Yuki Iwai <[email protected]>

Author: tenzen-y

content/en/docs/components/katib/experiment.md

@@ -282,8 +282,7 @@ use when combinatorial exploration is not possible. If the number of continuous
 variables is high, you should use quasi random sampling instead.
 
 Katib uses the [Hyperopt](http://hyperopt.github.io/hyperopt/),
-[Goptuna](https://github.com/c-bata/goptuna),
-[Chocolate](https://chocolate.readthedocs.io) or
+[Goptuna](https://github.com/c-bata/goptuna) or
 [Optuna](https://github.com/optuna/optuna) optimization
 framework for its random search.
 
@@ -325,8 +324,7 @@ steps, making it a good choice when the time to
 complete the evaluation of a parameter configuration is long.
 
 Katib uses the
-[Scikit-Optimize](https://github.com/scikit-optimize/scikit-optimize) or
-[Chocolate](https://chocolate.readthedocs.io) optimization framework
+[Scikit-Optimize](https://github.com/scikit-optimize/scikit-optimize) optimization framework
 for its Bayesian search. Scikit-Optimize is also known as `skopt`.
 
 Katib supports the following algorithm settings:

content/en/docs/components/katib/katib-config.md

@@ -182,11 +182,6 @@ any other settings, a default value is set automatically.
            <td><code>random</code>, <code>tpe</code></td>
            <td><a href="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/hyperopt/hyperopt">Hyperopt</a> optimization framework</td>
          </tr>
-         <tr>
-           <td><code>suggestion-chocolate</code></td>
-           <td><code>grid</code>, <code>random</code>, <code>quasirandom</code>, <code>bayesianoptimization</code>, <code>mocmaes</code></td>
-           <td><a href="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/AIworx-Labs/chocolate">Chocolate</a> optimization framework</td>
-         </tr>
          <tr>
            <td><code>suggestion-skopt</code></td>
            <td><code>bayesianoptimization</code></td>