diff --git a/examples/v1beta1/hp-tuning/hyperopt-distribution.yaml b/examples/v1beta1/hp-tuning/hyperopt-distribution.yaml
index 5d0a25c6f3d..f78e39ff3c7 100644
--- a/examples/v1beta1/hp-tuning/hyperopt-distribution.yaml
+++ b/examples/v1beta1/hp-tuning/hyperopt-distribution.yaml
@@ -11,9 +11,9 @@ spec:
     objectiveMetricName: loss
   algorithm:
     algorithmName: random
-  parallelTrialCount: 2
-  maxTrialCount: 2
-  maxFailedTrialCount: 2
+  parallelTrialCount: 3
+  maxTrialCount: 12
+  maxFailedTrialCount: 3
   parameters:
     - name: lr
       parameterType: double
diff --git a/pkg/suggestion/v1beta1/hyperopt/base_service.py b/pkg/suggestion/v1beta1/hyperopt/base_service.py
index 5b2c3d042a0..a46aa2476cf 100644
--- a/pkg/suggestion/v1beta1/hyperopt/base_service.py
+++ b/pkg/suggestion/v1beta1/hyperopt/base_service.py
@@ -64,83 +64,7 @@ def create_hyperopt_domain(self):
         # hyperopt.hp.uniform('x2', -10, 10)}
         hyperopt_search_space = {}
         for param in self.search_space.params:
-            if param.type == INTEGER:
-                if param.distribution == api_pb2.UNIFORM or param.distribution is None:
-                    if param.step:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.quniform(
-                                param.name,
-                                float(param.min),
-                                float(param.max),
-                                float(param.step),
-                            )
-                        )
-                    else:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.uniformint(
-                                param.name, float(param.min), float(param.max)
-                            )
-                        )
-                elif param.distribution == api_pb2.LOG_UNIFORM:
-                    if param.step:
-                        hyperopt_search_space[param.name] = hyperopt.hp.qloguniform(
-                            param.name,
-                            math.log(float(param.min)),
-                            math.log(float(param.max)),
-                            float(param.step),
-                        )
-                    else:
-                        hyperopt_search_space[param.name] = hyperopt.hp.loguniform(
-                            param.name,
-                            math.log(float(param.min)),
-                            math.log(float(param.max)),
-                        )
-                elif param.distribution == api_pb2.NORMAL:
-                    mu = (float(param.min) + float(param.max)) / 2
-                    sigma = (float(param.max) - float(param.min)) / 6
-
-                    if param.step:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.qnormal(
-                                param.name,
-                                mu,
-                                sigma,
-                                float(param.step),
-                            )
-                        )
-                    else:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.normal(
-                                param.name,
-                                mu,
-                                sigma,
-                            )
-                        )
-                elif param.distribution == api_pb2.LOG_NORMAL:
-                    log_min = math.log(float(param.min))
-                    log_max = math.log(float(param.max))
-
-                    mu = (log_min + log_max) / 2
-                    sigma = (log_max - log_min) / 6
-
-                    if param.step:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.qlognormal(
-                                param.name,
-                                mu,
-                                sigma,
-                                float(param.step),
-                            )
-                        )
-                    else:
-                        hyperopt_search_space[param.name] = int(
-                            hyperopt.hp.lognormal(
-                                param.name,
-                                mu,
-                                sigma,
-                            )
-                        )
-            elif param.type == DOUBLE:
+            if param.type in [INTEGER, DOUBLE]:
                 if param.distribution == api_pb2.UNIFORM or param.distribution is None:
                     if param.step:
                         hyperopt_search_space[param.name] = hyperopt.hp.quniform(
@@ -150,9 +74,14 @@ def create_hyperopt_domain(self):
                             float(param.step),
                         )
                     else:
-                        hyperopt_search_space[param.name] = hyperopt.hp.uniform(
-                            param.name, float(param.min), float(param.max)
-                        )
+                        if param.type == INTEGER:
+                            hyperopt_search_space[param.name] = hyperopt.hp.uniformint(
+                                param.name, float(param.min), float(param.max)
+                            )
+                        else:
+                            hyperopt_search_space[param.name] = hyperopt.hp.uniform(
+                                param.name, float(param.min), float(param.max)
+                            )
                 elif param.distribution == api_pb2.LOG_UNIFORM:
                     if param.step:
                         hyperopt_search_space[param.name] = hyperopt.hp.qloguniform(