diff --git a/python/cuml/cuml/cluster/dbscan.pyx b/python/cuml/cuml/cluster/dbscan.pyx
index 73de161853..0b042a98f8 100644
--- a/python/cuml/cuml/cluster/dbscan.pyx
+++ b/python/cuml/cuml/cluster/dbscan.pyx
@@ -386,7 +386,7 @@ class DBSCAN(Base,
 
         cdef float eps = self.eps
         cdef int min_samples = self.min_samples
-        cdef level_enum verbose = self.verbose
+        cdef level_enum verbose = self._verbose_level
         cdef bool multi_gpu = self._multi_gpu
         cdef size_t max_mbytes_per_batch = self.max_mbytes_per_batch or 0
 
diff --git a/python/cuml/cuml/cluster/kmeans.pyx b/python/cuml/cuml/cluster/kmeans.pyx
index e90b35324f..7c4e3af371 100644
--- a/python/cuml/cuml/cluster/kmeans.pyx
+++ b/python/cuml/cuml/cluster/kmeans.pyx
@@ -25,7 +25,6 @@ from libcpp cimport bool
 from pylibraft.common.handle cimport handle_t
 
 cimport cuml.cluster.cpp.kmeans as lib
-from cuml.internals.logger cimport level_enum
 from cuml.metrics.distance_type cimport DistanceType
 
 
@@ -36,7 +35,7 @@ cdef _kmeans_init_params(kmeans, lib.KMeansParams& params):
     params.n_clusters = kmeans.n_clusters
     params.max_iter = kmeans.max_iter
     params.tol = kmeans.tol
-    params.verbosity = <level_enum>(<int>kmeans.verbose)
+    params.verbosity = kmeans._verbose_level
     params.metric = DistanceType.L2Expanded
     params.batch_samples = int(kmeans.max_samples_per_batch)
     params.oversampling_factor = kmeans.oversampling_factor
diff --git a/python/cuml/cuml/ensemble/randomforest_common.pyx b/python/cuml/cuml/ensemble/randomforest_common.pyx
index 5b5d4a8578..7535c89d17 100644
--- a/python/cuml/cuml/ensemble/randomforest_common.pyx
+++ b/python/cuml/cuml/ensemble/randomforest_common.pyx
@@ -187,7 +187,6 @@ class BaseRandomForestModel(Base, InteropMixin):
             "min_impurity_decrease",
             "max_batch_size",
             "random_state",
-            "criterion",
             "n_streams",
             "oob_score",
             "handle",
@@ -421,7 +420,7 @@ class BaseRandomForestModel(Base, InteropMixin):
         cdef uintptr_t y_ptr = y.ptr
         cdef int n_rows = X.shape[0]
         cdef int n_cols = X.shape[1]
-        cdef level_enum verbose = <level_enum> self.verbose
+        cdef level_enum verbose = <level_enum> self._verbose_level
         cdef int n_classes = self.n_classes_ if is_classifier else 0
 
         if self.max_depth <= 0:
diff --git a/python/cuml/cuml/experimental/linear_model/lars.pyx b/python/cuml/cuml/experimental/linear_model/lars.pyx
index 12b1b67a30..6455fe17ee 100644
--- a/python/cuml/cuml/experimental/linear_model/lars.pyx
+++ b/python/cuml/cuml/experimental/linear_model/lars.pyx
@@ -262,13 +262,13 @@ class Lars(Base, RegressorMixin):
             larsFit(handle_[0], <float*> X_ptr, n_rows, <int> self.n_cols,
                     <float*> y_ptr, <float*> beta_ptr, <int*> active_idx_ptr,
                     <float*> alphas_ptr, &n_active, <float*> Gram_ptr,
-                    max_iter, <float*> coef_path_ptr, self.verbose, ld_X,
+                    max_iter, <float*> coef_path_ptr, self._verbose_level, ld_X,
                     ld_G, <float> self.eps)
         else:
             larsFit(handle_[0], <double*> X_ptr, n_rows, <int> self.n_cols,
                     <double*> y_ptr, <double*> beta_ptr, <int*> active_idx_ptr,
                     <double*> alphas_ptr, &n_active, <double*> Gram_ptr,
-                    max_iter, <double*> coef_path_ptr, self.verbose,
+                    max_iter, <double*> coef_path_ptr, self._verbose_level,
                     ld_X, ld_G, <double> self.eps)
         self.n_active = n_active
         self.n_iter_ = n_active
diff --git a/python/cuml/cuml/internals/base.py b/python/cuml/cuml/internals/base.py
index 1ef59fa82a..959e4d1b5a 100644
--- a/python/cuml/cuml/internals/base.py
+++ b/python/cuml/cuml/internals/base.py
@@ -14,8 +14,6 @@
 import cuml.internals.input_utils
 import cuml.internals.logger as logger
 import cuml.internals.nvtx as nvtx
-from cuml.internals import api_context_managers
-from cuml.internals.global_settings import GlobalSettings
 from cuml.internals.input_utils import determine_array_type
 from cuml.internals.mixins import TagsMixin
 from cuml.internals.output_type import (
@@ -24,40 +22,6 @@
 )
 
 
-class VerbosityDescriptor:
-    """Descriptor for ensuring correct type is used for verbosity
-
-    This descriptor ensures that when the 'verbose' attribute of a cuML
-    estimator is accessed external to the cuML API, an integer is returned
-    (consistent with Scikit-Learn's API for verbosity). Internal to the API, an
-    enum is used. Scikit-Learn's numerical values for verbosity are the inverse
-    of those used by spdlog, so the numerical value is also inverted internal
-    to the cuML API. This ensures that cuML code treats verbosity values as
-    expected for an spdlog-based codebase.
-    """
-
-    def __get__(self, obj, cls=None):
-        if api_context_managers.in_internal_api():
-            return logger._verbose_to_level(obj._verbose)
-        else:
-            return obj._verbose
-
-    def __set__(self, obj, value):
-        if api_context_managers.in_internal_api():
-            assert isinstance(value, logger.level_enum), (
-                "The log level should always be provided as a level_enum, "
-                "not an integer"
-            )
-            obj._verbose = logger._verbose_from_level(value)
-        else:
-            if isinstance(value, logger.level_enum):
-                raise ValueError(
-                    "The log level should always be provided as an integer, "
-                    "not using the enum"
-                )
-            obj._verbose = value
-
-
 class Base(TagsMixin, metaclass=cuml.internals.BaseMetaClass):
     """
     Base class for all the ML algos. It handles some of the common operations
@@ -191,28 +155,10 @@ def __init__(
         verbose=False,
         output_type=None,
     ):
-        """
-        Constructor. All children must call init method of this base class.
-
-        """
         self.handle = (
             pylibraft.common.handle.Handle() if handle is None else handle
         )
-
-        # The following manipulation of the root_cm ensures that the verbose
-        # descriptor sees any set or get of the verbose attribute as happening
-        # internal to the cuML API. Currently, __init__ calls do not take place
-        # within an api context manager, so setting "verbose" here would
-        # otherwise appear to be external to the cuML API. This behavior will
-        # be corrected with the update of cuML's API context manager
-        # infrastructure in https://github.com/rapidsai/cuml/pull/6189.
-        GlobalSettings().prev_root_cm = GlobalSettings().root_cm
-        GlobalSettings().root_cm = True
-        self.verbose = logger._verbose_to_level(verbose)
-        # Please see above note on manipulation of the root_cm. This should be
-        # rendered unnecessary with https://github.com/rapidsai/cuml/pull/6189.
-        GlobalSettings().root_cm = GlobalSettings().prev_root_cm
-
+        self.verbose = verbose
         self.output_type = _check_output_type_str(
             cuml.global_settings.output_type
             if output_type is None
@@ -224,8 +170,6 @@ def __init__(
         if nvtx_benchmark and nvtx_benchmark.lower() == "true":
             self.set_nvtx_annotations()
 
-    verbose = VerbosityDescriptor()
-
     def __repr__(self):
         """
         Pretty prints the arguments of a class using Scikit-learn standard :)
@@ -250,6 +194,11 @@ def __repr__(self):
             output += " <sk_model_ attribute used>"
         return output
 
+    @property
+    def _verbose_level(self):
+        """The current `verbose` setting as a `logger.level_enum`"""
+        return logger._verbose_to_level(self.verbose)
+
     @classmethod
     def _get_param_names(cls):
         """
@@ -267,20 +216,7 @@ def get_params(self, deep=True):
         need anything other than what is there in this method, then it doesn't
         have to override this method
         """
-        params = dict()
-        variables = self._get_param_names()
-        for key in variables:
-            var_value = getattr(self, key, None)
-            # We are currently internal to the cuML API, but the value we
-            # return will immediately be returned external to the API, so we
-            # must perform the translation from enum to integer before
-            # returning the value. Ordinarily, this is handled by
-            # VerbosityDescriptor for direct access to the verbose
-            # attribute.
-            if key == "verbose":
-                var_value = logger._verbose_from_level(var_value)
-            params[key] = var_value
-        return params
+        return {name: getattr(self, name) for name in self._get_param_names()}
 
     def set_params(self, **params):
         """
@@ -291,15 +227,13 @@ def set_params(self, **params):
         """
         if not params:
             return self
-        variables = self._get_param_names()
+        valid_params = self._get_param_names()
         for key, value in params.items():
-            if key not in variables:
-                raise ValueError("Bad param '%s' passed to set_params" % key)
-            else:
-                # Switch verbose to enum since we are now internal to cuML API
-                if key == "verbose":
-                    value = logger._verbose_to_level(value)
-                setattr(self, key, value)
+            if key not in valid_params:
+                raise ValueError(
+                    f"Invalid parameter {key!r} for `{type(self).__name__}`"
+                )
+            setattr(self, key, value)
         return self
 
     def _set_output_type(self, inp):
diff --git a/python/cuml/cuml/internals/logger.pyx b/python/cuml/cuml/internals/logger.pyx
index 96159aa26c..e0f9fdb83d 100644
--- a/python/cuml/cuml/internals/logger.pyx
+++ b/python/cuml/cuml/internals/logger.pyx
@@ -2,11 +2,6 @@
 # SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
 # SPDX-License-Identifier: Apache-2.0
 #
-
-# distutils: language = c++
-
-
-import logging
 import sys
 
 
@@ -23,6 +18,7 @@ cdef void _log_callback(int lvl, const char * msg) with gil:
     """
     print(msg.decode('utf-8'), end='')
 
+
 cdef void _log_flush() with gil:
     """
     Default spdlogs callback function to flush logs
@@ -38,12 +34,7 @@ def _verbose_to_level(verbose: bool | int) -> level_enum:
     elif verbose is False:
         return level_enum.info
     else:
-        return level_enum(6 - verbose)
-
-
-def _verbose_from_level(level: level_enum) -> int:
-    """Convert a `level_enum` back into an equivalent `verbose` parameter value."""
-    return 6 - int(level)
+        return level_enum(min(max(6 - verbose, 0), 6))
 
 
 cdef class LogLevelSetter:
@@ -179,7 +170,7 @@ def should_log_for(level):
     return default_logger().should_log(level)
 
 
-def _log(level_enum lvl, msg, default_func):
+def _log(level_enum lvl, msg):
     """
     Internal function to log a message at a given level.
 
@@ -189,8 +180,6 @@ def _log(level_enum lvl, msg, default_func):
         Logging level to be set.
     msg : str
         Message to be logged.
-    default_func : function
-        Default logging function to be used if GPU build is disabled.
     """
     cdef string s = msg.encode("UTF-8")
     default_logger().log(lvl, s)
@@ -200,115 +189,73 @@ def trace(msg):
     """
     Logs a trace message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.trace("Hello world! This is a trace message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
     # No trace level in Python so we use the closest thing, debug.
-    _log(level_enum.trace, msg, logging.debug)
+    _log(level_enum.trace, msg)
 
 
 def debug(msg):
     """
     Logs a debug message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.debug("Hello world! This is a debug message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
-    _log(level_enum.debug, msg, logging.debug)
+    _log(level_enum.debug, msg)
 
 
 def info(msg):
     """
     Logs an info message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.info("Hello world! This is a info message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
-    _log(level_enum.info, msg, logging.info)
+    _log(level_enum.info, msg)
 
 
 def warn(msg):
     """
     Logs a warning message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.warn("Hello world! This is a warning message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
-    _log(level_enum.warn, msg, logging.warn)
+    _log(level_enum.warn, msg)
 
 
 def error(msg):
     """
     Logs an error message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.error("Hello world! This is a error message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
-    _log(level_enum.error, msg, logging.error)
+    _log(level_enum.error, msg)
 
 
 def critical(msg):
     """
     Logs a critical message, if it is enabled.
 
-    Examples
-    --------
-
-    .. code-block:: python
-
-                logger.critical("Hello world! This is a critical message")
-
     Parameters
     ----------
     msg : str
         Message to be logged.
     """
-    _log(level_enum.critical, msg, logging.critical)
+    _log(level_enum.critical, msg)
 
 
 def flush():
diff --git a/python/cuml/cuml/linear_model/elastic_net.py b/python/cuml/cuml/linear_model/elastic_net.py
index 26ae869616..b6dfe2c40e 100644
--- a/python/cuml/cuml/linear_model/elastic_net.py
+++ b/python/cuml/cuml/linear_model/elastic_net.py
@@ -265,7 +265,7 @@ def fit(
                 max_iter=self.max_iter,
                 tol=self.tol,
                 penalty_normalized=False,
-                verbose=self.verbose,
+                verbose=self._verbose_level,
                 handle=self.handle,
             )
             coef = CumlArray(data=coef.to_output("cupy").flatten())
diff --git a/python/cuml/cuml/linear_model/logistic_regression.py b/python/cuml/cuml/linear_model/logistic_regression.py
index 86c6cabf2d..8dd1921d6f 100644
--- a/python/cuml/cuml/linear_model/logistic_regression.py
+++ b/python/cuml/cuml/linear_model/logistic_regression.py
@@ -312,7 +312,7 @@ def fit(
             max_iter=self.max_iter,
             tol=self.tol,
             linesearch_max_iter=self.linesearch_max_iter,
-            verbose=self.verbose,
+            verbose=self._verbose_level,
             handle=self.handle,
             lbfgs_memory=self.lbfgs_memory,
             penalty_normalized=self.penalty_normalized,
diff --git a/python/cuml/cuml/linear_model/logistic_regression_mg.pyx b/python/cuml/cuml/linear_model/logistic_regression_mg.pyx
index 5d57a1f235..890e274669 100644
--- a/python/cuml/cuml/linear_model/logistic_regression_mg.pyx
+++ b/python/cuml/cuml/linear_model/logistic_regression_mg.pyx
@@ -186,7 +186,7 @@ class LogisticRegressionMG(MGFitMixin, LogisticRegression):
             linesearch_max_iter=self.linesearch_max_iter,
             lbfgs_memory=self.lbfgs_memory,
             penalty_normalized=self.penalty_normalized,
-            verbose=self.verbose,
+            verbose=self._verbose_level,
         )
 
         # Allocate outputs
diff --git a/python/cuml/cuml/manifold/t_sne.pyx b/python/cuml/cuml/manifold/t_sne.pyx
index be534adbc7..ee1a9029e2 100644
--- a/python/cuml/cuml/manifold/t_sne.pyx
+++ b/python/cuml/cuml/manifold/t_sne.pyx
@@ -253,7 +253,7 @@ cdef _init_params(self, int n_samples, TSNEParams &params):
     params.pre_momentum = pre_momentum
     params.post_momentum = post_momentum
     params.random_state = seed
-    params.verbosity = self.verbose
+    params.verbosity = self._verbose_level
     params.square_distances = self.square_distances
     params.algorithm = algo
     params.init = init
diff --git a/python/cuml/cuml/manifold/umap/umap.pyx b/python/cuml/cuml/manifold/umap/umap.pyx
index a0a28c16a2..acac8abda2 100644
--- a/python/cuml/cuml/manifold/umap/umap.pyx
+++ b/python/cuml/cuml/manifold/umap/umap.pyx
@@ -337,7 +337,7 @@ cdef init_params(self, lib.UMAPParams &params, n_rows, is_sparse=False, is_fit=T
     params.repulsion_strength = self.repulsion_strength
     params.negative_sample_rate = self.negative_sample_rate
     params.transform_queue_size = self.transform_queue_size
-    params.verbosity = self.verbose
+    params.verbosity = self._verbose_level
     params.a = self._a
     params.b = self._b
     params.target_n_neighbors = self.target_n_neighbors
diff --git a/python/cuml/cuml/solvers/qn.pyx b/python/cuml/cuml/solvers/qn.pyx
index 6b0c4cab0c..ccc548ef4f 100644
--- a/python/cuml/cuml/solvers/qn.pyx
+++ b/python/cuml/cuml/solvers/qn.pyx
@@ -561,7 +561,7 @@ class QN(Base):
             lbfgs_memory=self.lbfgs_memory,
             penalty_normalized=self.penalty_normalized,
             init_coef=init_coef,
-            verbose=self.verbose,
+            verbose=self._verbose_level,
             handle=self.handle,
         )
         self.coef_ = coef
diff --git a/python/cuml/cuml/svm/linear.pyx b/python/cuml/cuml/svm/linear.pyx
index 552cdf0cae..c9ab8f6815 100644
--- a/python/cuml/cuml/svm/linear.pyx
+++ b/python/cuml/cuml/svm/linear.pyx
@@ -99,7 +99,7 @@ def fit(
     C,
     tol,
     epsilon,
-    verbose,
+    level_enum verbose,
 ):
     """Perform a Linear SVR or SVC fit.
 
@@ -173,7 +173,7 @@ def fit(
     params.epsilon = epsilon
     params.grad_tol = tol
     params.change_tol = 0.1 * tol
-    params.verbose = <level_enum>verbose
+    params.verbose = verbose
 
     # Extract dimensions
     cdef size_t n_rows = X.shape[0]
diff --git a/python/cuml/cuml/svm/linear_svc.py b/python/cuml/cuml/svm/linear_svc.py
index ab699af0b4..45f2b48de6 100644
--- a/python/cuml/cuml/svm/linear_svc.py
+++ b/python/cuml/cuml/svm/linear_svc.py
@@ -281,7 +281,7 @@ def fit(
             C=self.C,
             tol=self.tol,
             epsilon=0.0,
-            verbose=self.verbose,
+            verbose=self._verbose_level,
         )
         self.coef_ = coef
         self.intercept_ = intercept
diff --git a/python/cuml/cuml/svm/linear_svr.py b/python/cuml/cuml/svm/linear_svr.py
index 52df6537c6..62798eef57 100644
--- a/python/cuml/cuml/svm/linear_svr.py
+++ b/python/cuml/cuml/svm/linear_svr.py
@@ -252,7 +252,7 @@ def fit(
             C=self.C,
             tol=self.tol,
             epsilon=self.epsilon,
-            verbose=self.verbose,
+            verbose=self._verbose_level,
         )
         self.coef_ = coef
         self.intercept_ = intercept
diff --git a/python/cuml/cuml/svm/svm_base.pyx b/python/cuml/cuml/svm/svm_base.pyx
index 99815bca67..33fc453f31 100644
--- a/python/cuml/cuml/svm/svm_base.pyx
+++ b/python/cuml/cuml/svm/svm_base.pyx
@@ -397,7 +397,7 @@ class SVMBase(Base,
         param.cache_size = self.cache_size
         param.nochange_steps = self.nochange_steps
         param.tol = self.tol
-        param.verbosity = self.verbose
+        param.verbosity = self._verbose_level
         param.epsilon = self.epsilon
         param.svmType = lib.SvmType.C_SVC if is_classifier else lib.SvmType.EPSILON_SVR
 
diff --git a/python/cuml/tests/test_hdbscan.py b/python/cuml/tests/test_hdbscan.py
index f86e4e9785..c6d876c8ac 100644
--- a/python/cuml/tests/test_hdbscan.py
+++ b/python/cuml/tests/test_hdbscan.py
@@ -1,7 +1,6 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2025, NVIDIA CORPORATION.
 # SPDX-License-Identifier: Apache-2.0
 #
-
 import cupy as cp
 import hdbscan
 import numpy as np
@@ -20,7 +19,6 @@
     membership_vector,
 )
 from cuml.cluster.hdbscan.hdbscan import _condense_hierarchy, _extract_clusters
-from cuml.internals import logger
 from cuml.metrics import adjusted_rand_score
 from cuml.testing.datasets import make_pattern
 from cuml.testing.utils import array_equal
@@ -166,7 +164,6 @@ def test_hdbscan_blobs(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         min_samples=min_samples,
         max_cluster_size=max_cluster_size,
@@ -225,7 +222,6 @@ def test_hdbscan_sklearn_datasets(
     X = supervised_learning_dataset
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         gen_min_span_tree=True,
         min_samples=min_samples,
@@ -326,7 +322,6 @@ def test_hdbscan_cluster_patterns(
     X, y = make_pattern(dataset, nrows)[0]
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         min_samples=min_samples,
         max_cluster_size=max_cluster_size,
@@ -526,7 +521,6 @@ def test_all_points_membership_vectors_blobs(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
         min_cluster_size=min_cluster_size,
@@ -576,7 +570,6 @@ def test_all_points_membership_vectors_moons(
     X, y = datasets.make_moons(n_samples=nrows, noise=0.05, random_state=42)
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         min_samples=min_samples,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
@@ -632,7 +625,6 @@ def test_all_points_membership_vectors_circles(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         min_samples=min_samples,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
@@ -704,7 +696,6 @@ def test_approximate_predict_blobs(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
         min_cluster_size=min_cluster_size,
@@ -762,7 +753,6 @@ def test_approximate_predict_moons(
     X_test = X[nrows:]
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         min_samples=min_samples,
         max_cluster_size=max_cluster_size,
@@ -827,7 +817,6 @@ def test_approximate_predict_circles(
     X_test = X[nrows:]
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         min_samples=min_samples,
         max_cluster_size=max_cluster_size,
@@ -893,7 +882,6 @@ def test_approximate_predict_digits(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         min_samples=min_samples,
         max_cluster_size=max_cluster_size,
@@ -967,7 +955,6 @@ def test_membership_vector_blobs(
     )
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
         min_cluster_size=min_cluster_size,
@@ -1030,7 +1017,6 @@ def test_membership_vector_moons(
     X_test = X[nrows:]
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         min_samples=min_samples,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
@@ -1094,7 +1080,6 @@ def test_membership_vector_circles(
     X_test = X[nrows:]
 
     cuml_agg = HDBSCAN(
-        verbose=logger.level_enum.info,
         min_samples=min_samples,
         allow_single_cluster=allow_single_cluster,
         max_cluster_size=max_cluster_size,
diff --git a/python/cuml/tests/test_logger.py b/python/cuml/tests/test_logger.py
index 8827da59da..1c31427d1d 100644
--- a/python/cuml/tests/test_logger.py
+++ b/python/cuml/tests/test_logger.py
@@ -11,22 +11,23 @@
 
 
 @pytest.mark.parametrize(
-    "verbose, level, verbose_numeric",
+    "verbose, level",
     [
-        (False, logger.level_enum.info, 4),
-        (True, logger.level_enum.debug, 5),
-        (0, logger.level_enum.off, 0),
-        (1, logger.level_enum.critical, 1),
-        (2, logger.level_enum.error, 2),
-        (3, logger.level_enum.warn, 3),
-        (4, logger.level_enum.info, 4),
-        (5, logger.level_enum.debug, 5),
-        (6, logger.level_enum.trace, 6),
+        (False, logger.level_enum.info),
+        (True, logger.level_enum.debug),
+        (-1, logger.level_enum.off),
+        (0, logger.level_enum.off),
+        (1, logger.level_enum.critical),
+        (2, logger.level_enum.error),
+        (3, logger.level_enum.warn),
+        (4, logger.level_enum.info),
+        (5, logger.level_enum.debug),
+        (6, logger.level_enum.trace),
+        (10, logger.level_enum.trace),
     ],
 )
-def test_verbose_to_from_level(verbose, level, verbose_numeric):
+def test_verbose_to_level(verbose, level):
     assert logger._verbose_to_level(verbose) == level
-    assert logger._verbose_from_level(level) == verbose_numeric
 
 
 def test_logger():
diff --git a/python/cuml/tests/test_umap.py b/python/cuml/tests/test_umap.py
index 053d8fe38f..a66c48dc34 100644
--- a/python/cuml/tests/test_umap.py
+++ b/python/cuml/tests/test_umap.py
@@ -19,7 +19,7 @@
 from sklearn.neighbors import NearestNeighbors
 
 import cuml
-from cuml.internals import GraphBasedDimRedCallback, logger
+from cuml.internals import GraphBasedDimRedCallback
 from cuml.manifold.umap import UMAP as cuUMAP
 from cuml.metrics import pairwise_distances
 from cuml.testing.utils import (
@@ -181,7 +181,6 @@ def test_umap_transform_on_digits_sparse(
 
     fitter = cuUMAP(
         n_neighbors=15,
-        verbose=logger.level_enum.info,
         init="random",
         n_epochs=0,
         min_dist=0.01,
@@ -219,7 +218,6 @@ def test_umap_transform_on_digits(target_metric):
 
     fitter = cuUMAP(
         n_neighbors=15,
-        verbose=logger.level_enum.debug,
         init="random",
         n_epochs=0,
         min_dist=0.01,