diff --git a/numalogic/config/factory.py b/numalogic/config/factory.py
index 6284d6b3..27bd94a4 100644
--- a/numalogic/config/factory.py
+++ b/numalogic/config/factory.py
@@ -63,12 +63,14 @@ class PostprocessFactory(_ObjectFactory):
 class ThresholdFactory(_ObjectFactory):
     """Factory class to create threshold instances."""
 
-    from numalogic.models.threshold import StdDevThreshold, StaticThreshold, SigmoidThreshold
+    from numalogic.models.threshold import \
+        StdDevThreshold, MahalanobisThreshold, StaticThreshold, SigmoidThreshold
 
     _CLS_MAP: ClassVar[dict] = {
         "StdDevThreshold": StdDevThreshold,
         "StaticThreshold": StaticThreshold,
         "SigmoidThreshold": SigmoidThreshold,
+        "MahalanobisThreshold": MahalanobisThreshold,
     }
 
 
diff --git a/numalogic/models/threshold/__init__.py b/numalogic/models/threshold/__init__.py
index ba26f79b..d7892e1f 100644
--- a/numalogic/models/threshold/__init__.py
+++ b/numalogic/models/threshold/__init__.py
@@ -1,4 +1,5 @@
 from numalogic.models.threshold._std import StdDevThreshold
+from numalogic.models.threshold._mahalanobis import MahalanobisThreshold
 from numalogic.models.threshold._static import StaticThreshold, SigmoidThreshold
 
-__all__ = ["StdDevThreshold", "StaticThreshold", "SigmoidThreshold"]
+__all__ = ["StdDevThreshold", "StaticThreshold", "SigmoidThreshold", "MahalanobisThreshold"]
diff --git a/numalogic/models/threshold/_mahalanobis.py b/numalogic/models/threshold/_mahalanobis.py
new file mode 100644
index 00000000..756f807a
--- /dev/null
+++ b/numalogic/models/threshold/_mahalanobis.py
@@ -0,0 +1,145 @@
+from typing import Final
+
+import numpy as np
+import numpy.typing as npt
+
+from numalogic.base import BaseThresholdModel
+from typing_extensions import Self
+
+from numalogic.tools.exceptions import ModelInitializationError
+
+_INLIER: Final[int] = 0
+_OUTLIER: Final[int] = 1
+
+
+class MahalanobisThreshold(BaseThresholdModel):
+    """
+    Multivariate threshold estimator using Mahalanobis distance.
+
+    The maximum outlier probability is used to calculate the k value
+    using Chebyshev's inequality. This basically means that the
+    probability of values lying outside the interval
+    (mean - k * std, mean + k * std) is not more than max_outlier_prob.
+    A value of 0.1 means that 90% of the values lie within the interval and
+    10% of the values lie outside the interval.
+
+    The threshold is calculated as the
+    mean of Mahalanobis distance plus k times the standard deviation
+    of Mahalanobis distance.
+
+    Args:
+    ----
+        max_outlier_prob: maximum outlier probability (default: 0.1)
+
+    Raises
+    ------
+        ValueError: if max_outlier_prob is not in range (0, 1)
+    """
+
+    def __init__(self, max_outlier_prob: float = 0.1):
+        if not 0.0 < max_outlier_prob < 1.0:
+            raise ValueError("max_outlier_prob should be in range (0, 1)")
+        self._k = self._chebyshev_k(max_outlier_prob)
+        self._distr_mean = None
+        self._cov_inv = None
+        self._md_thresh = None
+        self._is_fitted = False
+
+    @property
+    def threshold(self):
+        """Returns the threshold value."""
+        return self._md_thresh
+
+    @property
+    def std_factor(self):
+        """Returns the k value calculated using Chebyshev's inequality."""
+        return self._k
+
+    @staticmethod
+    def _chebyshev_k(p: float) -> float:
+        """Calculate the k value using Chebyshev's inequality."""
+        return np.reciprocal(np.sqrt(p))
+
+    def fit(self, x: npt.NDArray[float]) -> Self:
+        """
+        Fit the estimator on the training set.
+
+        Args:
+        ----
+            x: training data
+
+        Returns
+        -------
+            self
+        """
+        self._distr_mean = np.mean(x, axis=0)
+        cov = np.cov(x, rowvar=False)
+        self._cov_inv = np.linalg.inv(cov)
+        mahal_dist = self.mahalanobis(x)
+        self._md_thresh = np.mean(mahal_dist) + self._k * np.std(mahal_dist)
+        self._is_fitted = True
+        return self
+
+    def mahalanobis(self, x: npt.NDArray[float]) -> npt.NDArray[float]:
+        """
+        Calculate the Mahalanobis distance.
+
+        Args:
+        ----
+            x: input data
+
+        Returns
+        -------
+            Mahalanobis distance vector
+        """
+        x_distance = x - self._distr_mean
+        mahal_grid = x_distance @ self._cov_inv @ x_distance.T
+        return np.sqrt(np.diagonal(mahal_grid))
+
+    def predict(self, x: npt.NDArray[float]) -> npt.NDArray[int]:
+        """
+        Returns an integer array of same shape as input.
+        0 denotes inlier, 1 denotes outlier.
+
+        Args:
+        ----
+            x: input data
+
+        Returns
+        -------
+            Integer Array of 0s and 1s
+
+        Raises
+        ------
+            RuntimeError: if the model is not fitted yet
+        """
+        if not self._is_fitted:
+            raise ModelInitializationError("Model not fitted yet.")
+        md = self.mahalanobis(x)
+        y_hat = np.zeros_like(x)
+        y_hat[md < self._md_thresh] = _INLIER
+        y_hat[md >= self._md_thresh] = _OUTLIER
+        return y_hat
+
+    def score_samples(self, x: npt.NDArray[float]) -> npt.NDArray[float]:
+        """
+        Returns the outlier score for each sample.
+
+        Score is calculated as the ratio of Mahalanobis distance to threshold.
+        A score greater than 1.0 means that the sample is an outlier.
+
+        Args:
+        ----
+            x: input data
+
+        Returns
+        -------
+            Outlier score for each sample
+
+        Raises
+        ------
+            RuntimeError: if the model is not fitted yet
+        """
+        if not self._is_fitted:
+            raise ModelInitializationError("Model not fitted yet.")
+        return self.mahalanobis(x) / self._md_thresh
diff --git a/numalogic/registry/dynamodb_registry.py b/numalogic/registry/dynamodb_registry.py
index 4ff4432d..3ee1d49f 100644
--- a/numalogic/registry/dynamodb_registry.py
+++ b/numalogic/registry/dynamodb_registry.py
@@ -80,7 +80,8 @@ class DynamoDBRegistry(ArtifactManager):
         role: AWS role with access to DynamoDB table
         models_to_retain: number of models to retain in the DB (default = 2)
         cache_registry: ArtifactCache instance, must have an expiration set for the
-         model to be refreshed
+         model to be refreshed.
+
     Examples
     --------
     >>> from numalogic.models.autoencoder.variants import VanillaAE
diff --git a/poetry.lock b/poetry.lock
index a272d2ee..c22f24f1 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,98 +2,98 @@
 
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 name = "aiohttp"
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+version = "3.8.5"
 description = "Async http client/server framework (asyncio)"
 optional = false
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+    {file = "aiohttp-3.8.5.tar.gz", hash = "sha256:b9552ec52cc147dbf1944ac7ac98af7602e51ea2dcd076ed194ca3c0d1c7d0bc"},
 ]
 
 [package.dependencies]
@@ -265,6 +265,20 @@ six = "*"
 [package.extras]
 test = ["astroid", "pytest"]
 
+[[package]]
+name = "async-lru"
+version = "2.0.3"
+description = "Simple LRU cache for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "async-lru-2.0.3.tar.gz", hash = "sha256:b714c9d1415fca4e264da72a9e2abc66880ce7430e03a973341f88ea4c0d4869"},
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+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "async-timeout"
 version = "4.0.2"
@@ -294,6 +308,17 @@ docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-
 tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 
+[[package]]
+name = "babel"
+version = "2.12.1"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Babel-2.12.1-py3-none-any.whl", hash = "sha256:b4246fb7677d3b98f501a39d43396d3cafdc8eadb045f4a31be01863f655c610"},
+    {file = "Babel-2.12.1.tar.gz", hash = "sha256:cc2d99999cd01d44420ae725a21c9e3711b3aadc7976d6147f622d8581963455"},
+]
+
 [[package]]
 name = "backcall"
 version = "0.2.0"
@@ -325,36 +350,33 @@ lxml = ["lxml"]
 
 [[package]]
 name = "black"
-version = "23.3.0"
+version = "23.7.0"
 description = "The uncompromising code formatter."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
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+    {file = "black-23.7.0.tar.gz", hash = "sha256:022a582720b0d9480ed82576c920a8c1dde97cc38ff11d8d8859b3bd6ca9eedb"},
 ]
 
 [package.dependencies]
@@ -392,17 +414,17 @@ css = ["tinycss2 (>=1.1.0,<1.2)"]
 
 [[package]]
 name = "boto3"
-version = "1.28.0"
+version = "1.28.10"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "boto3-1.28.0-py3-none-any.whl", hash = "sha256:ef81f63d38be25137c3ae9c6db2841c4cde82d1c7da9f8cb9f42f410c242d4f2"},
-    {file = "boto3-1.28.0.tar.gz", hash = "sha256:8d43863e4769a5652efc32fd63430df58488cdb3fb85e614461b511358e47ec7"},
+    {file = "boto3-1.28.10-py3-none-any.whl", hash = "sha256:67001b3f512cbe2e00e352c65fb443b504e5e388fee39d73bcc42da1ae87d9e3"},
+    {file = "boto3-1.28.10.tar.gz", hash = "sha256:cb8af03f553f1c7db7137bc897785baeeaa97b8fde483eb1cdb1f1ef3cec9cb7"},
 ]
 
 [package.dependencies]
-botocore = ">=1.31.0,<1.32.0"
+botocore = ">=1.31.10,<1.32.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.6.0,<0.7.0"
 
@@ -411,13 +433,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.31.0"
+version = "1.31.10"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">= 3.7"
 files = [
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-    {file = "botocore-1.31.0.tar.gz", hash = "sha256:db22eea779de7f61621a612c6a36f3ee069a37d4572a9541aa374503447622aa"},
+    {file = "botocore-1.31.10-py3-none-any.whl", hash = "sha256:a3bfd3627a490faedf37d79373d6957936d7720888ca85466e0471cb921e4557"},
+    {file = "botocore-1.31.10.tar.gz", hash = "sha256:736a9412f405d6985570c4a87b533c2396dd8d4042d8c7a0ca14e73d4f1bcf9d"},
 ]
 
 [package.dependencies]
@@ -426,7 +448,7 @@ python-dateutil = ">=2.1,<3.0.0"
 urllib3 = ">=1.25.4,<1.27"
 
 [package.extras]
-crt = ["awscrt (==0.16.9)"]
+crt = ["awscrt (==0.16.26)"]
 
 [[package]]
 name = "cachetools"
@@ -441,13 +463,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.5.7"
+version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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+    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
 ]
 
 [[package]]
@@ -539,97 +561,97 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.1.0"
+version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 [package.dependencies]
@@ -811,30 +833,34 @@ toml = ["tomli"]
 
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 [[package]]
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 [[package]]
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-version = "3.1.31"
+version = "3.1.32"
 description = "GitPython is a Python library used to interact with Git repositories"
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 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
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 [[package]]
 name = "google-auth"
-version = "2.21.0"
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 [package.dependencies]
-grpcio = ">=1.56.0"
+grpcio = ">=1.56.2"
 protobuf = ">=4.21.6,<5.0dev"
 setuptools = "*"
 
@@ -1551,13 +1564,13 @@ files = [
 
 [[package]]
 name = "identify"
-version = "2.5.24"
+version = "2.5.26"
 description = "File identification library for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -1576,13 +1589,13 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "6.7.0"
+version = "6.8.0"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1591,25 +1604,25 @@ zipp = ">=0.5"
 [package.extras]
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 perf = ["ipython"]
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+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
 [[package]]
 name = "importlib-resources"
-version = "5.12.0"
+version = "6.0.0"
 description = "Read resources from Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.dependencies]
 zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
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+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
 
 [[package]]
 name = "iniconfig"
@@ -1624,13 +1637,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.24.0"
+version = "6.25.0"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1835,6 +1848,20 @@ files = [
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 ]
 
+[[package]]
+name = "json5"
+version = "0.9.14"
+description = "A Python implementation of the JSON5 data format."
+optional = false
+python-versions = "*"
+files = [
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+    {file = "json5-0.9.14.tar.gz", hash = "sha256:9ed66c3a6ca3510a976a9ef9b8c0787de24802724ab1860bc0153c7fdd589b02"},
+]
+
+[package.extras]
+dev = ["hypothesis"]
+
 [[package]]
 name = "jsonpointer"
 version = "2.4"
@@ -1847,13 +1874,13 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.18.0"
+version = "4.18.4"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "jsonschema-4.18.4.tar.gz", hash = "sha256:fb3642735399fa958c0d2aad7057901554596c63349f4f6b283c493cf692a25d"},
 ]
 
 [package.dependencies]
@@ -1876,13 +1903,13 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2023.6.1"
+version = "2023.7.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema_specifications-2023.6.1-py3-none-any.whl", hash = "sha256:3d2b82663aff01815f744bb5c7887e2121a63399b49b104a3c96145474d091d7"},
-    {file = "jsonschema_specifications-2023.6.1.tar.gz", hash = "sha256:ca1c4dd059a9e7b34101cf5b3ab7ff1d18b139f35950d598d629837ef66e8f28"},
+    {file = "jsonschema_specifications-2023.7.1-py3-none-any.whl", hash = "sha256:05adf340b659828a004220a9613be00fa3f223f2b82002e273dee62fd50524b1"},
+    {file = "jsonschema_specifications-2023.7.1.tar.gz", hash = "sha256:c91a50404e88a1f6ba40636778e2ee08f6e24c5613fe4c53ac24578a5a7f72bb"},
 ]
 
 [package.dependencies]
@@ -1999,6 +2026,21 @@ cli = ["click", "rich"]
 docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontrib-spelling"]
 test = ["click", "coverage", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "pytest-cov", "rich"]
 
+[[package]]
+name = "jupyter-lsp"
+version = "2.2.0"
+description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter-lsp-2.2.0.tar.gz", hash = "sha256:8ebbcb533adb41e5d635eb8fe82956b0aafbf0fd443b6c4bfa906edeeb8635a1"},
+    {file = "jupyter_lsp-2.2.0-py3-none-any.whl", hash = "sha256:9e06b8b4f7dd50300b70dd1a78c0c3b0c3d8fa68e0f2d8a5d1fbab62072aca3f"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+jupyter-server = ">=1.1.2"
+
 [[package]]
 name = "jupyter-server"
 version = "2.7.0"
@@ -2054,6 +2096,38 @@ terminado = ">=0.8.3"
 docs = ["jinja2", "jupyter-server", "mistune (<3.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
 test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
 
+[[package]]
+name = "jupyterlab"
+version = "4.0.3"
+description = "JupyterLab computational environment"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab-4.0.3-py3-none-any.whl", hash = "sha256:d369944391b1d15f2d1f3cb965fb67352956279b2ae6f03ce7947a43940a8301"},
+    {file = "jupyterlab-4.0.3.tar.gz", hash = "sha256:e14d1ce46a613028111d0d476a1d7d6b094003b7462bac669f5b478317abcb39"},
+]
+
+[package.dependencies]
+async-lru = ">=1.0.0"
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+ipykernel = "*"
+jinja2 = ">=3.0.3"
+jupyter-core = "*"
+jupyter-lsp = ">=2.0.0"
+jupyter-server = ">=2.4.0,<3"
+jupyterlab-server = ">=2.19.0,<3"
+notebook-shim = ">=0.2"
+packaging = "*"
+tomli = {version = "*", markers = "python_version < \"3.11\""}
+tornado = ">=6.2.0"
+traitlets = "*"
+
+[package.extras]
+dev = ["black[jupyter] (==23.3.0)", "build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.0.271)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-tornasync", "sphinx (>=1.8)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.0.1)", "ipython (==8.14.0)", "ipywidgets (==8.0.6)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.0.post0)", "matplotlib (==3.7.1)", "nbconvert (>=7.0.0)", "pandas (==2.0.2)", "scipy (==1.10.1)", "vega-datasets (==0.9.0)"]
+test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
+
 [[package]]
 name = "jupyterlab-pygments"
 version = "0.2.2"
@@ -2065,6 +2139,32 @@ files = [
     {file = "jupyterlab_pygments-0.2.2.tar.gz", hash = "sha256:7405d7fde60819d905a9fa8ce89e4cd830e318cdad22a0030f7a901da705585d"},
 ]
 
+[[package]]
+name = "jupyterlab-server"
+version = "2.24.0"
+description = "A set of server components for JupyterLab and JupyterLab like applications."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jupyterlab_server-2.24.0-py3-none-any.whl", hash = "sha256:5f077e142bb8dc9b843d960f940c513581bceca3793a0d80f9c67d9522c4e876"},
+    {file = "jupyterlab_server-2.24.0.tar.gz", hash = "sha256:4e6f99e0a5579bbbc32e449c4dbb039561d4f1a7827d5733273ed56738f21f07"},
+]
+
+[package.dependencies]
+babel = ">=2.10"
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+jinja2 = ">=3.0.3"
+json5 = ">=0.9.0"
+jsonschema = ">=4.17.3"
+jupyter-server = ">=1.21,<3"
+packaging = ">=21.3"
+requests = ">=2.28"
+
+[package.extras]
+docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi (>0.8)"]
+openapi = ["openapi-core (>=0.16.1,<0.17.0)", "ruamel-yaml"]
+test = ["hatch", "ipykernel", "jupyterlab-server[openapi]", "openapi-spec-validator (>=0.5.1,<0.7.0)", "pytest (>=7.0)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
+
 [[package]]
 name = "jupyterlab-widgets"
 version = "3.0.8"
@@ -2321,13 +2421,13 @@ files = [
 
 [[package]]
 name = "mlflow-skinny"
-version = "2.4.1"
+version = "2.5.0"
 description = "MLflow: A Platform for ML Development and Productionization"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "mlflow-skinny-2.4.1.tar.gz", hash = "sha256:ec5c8459a4bb1d0c619490dff0a3dce4949590a4bf76c77e0cb218143c33c29a"},
-    {file = "mlflow_skinny-2.4.1-py3-none-any.whl", hash = "sha256:b3226bbfdc5adcb7dcc2835c6956269641a07c9c2085d9f8f026bd577bd9660c"},
+    {file = "mlflow-skinny-2.5.0.tar.gz", hash = "sha256:cabb5213cdc68e540d5b8828f93d636c1ea5ac33a44288c8c5d05b65b7055747"},
+    {file = "mlflow_skinny-2.5.0-py3-none-any.whl", hash = "sha256:b2bef381fc7e842e1846debdd7261bdbf8f218bb88f2232092dd86dd2b06e9e1"},
 ]
 
 [package.dependencies]
@@ -2348,18 +2448,18 @@ sqlparse = ">=0.4.0,<1"
 aliyun-oss = ["aliyunstoreplugin"]
 databricks = ["azure-storage-file-datalake (>12)", "boto3 (>1)", "google-cloud-storage (>=1.30.0)"]
 extras = ["azureml-core (>=1.2.0)", "boto3", "google-cloud-storage (>=1.30.0)", "kubernetes", "mlserver (>=1.2.0,!=1.3.1)", "mlserver-mlflow (>=1.2.0,!=1.3.1)", "prometheus-flask-exporter", "pyarrow", "pysftp", "requests-auth-aws-sigv4", "virtualenv"]
-gateway = ["fastapi (<1)", "pydantic (>=1.0,<3)", "uvicorn (<1)"]
+gateway = ["aiohttp (<4)", "fastapi (<1)", "psutil (<6)", "pydantic (>=1.0,<2)", "uvicorn[standard] (<1)", "watchfiles (<1)"]
 sqlserver = ["mlflow-dbstore"]
 
 [[package]]
 name = "moto"
-version = "4.1.12"
+version = "4.1.13"
 description = ""
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "moto-4.1.12-py2.py3-none-any.whl", hash = "sha256:6f40141ff2f3a309c19faa169433afdf48d28733d328b08a843021ae36f005d9"},
-    {file = "moto-4.1.12.tar.gz", hash = "sha256:25577e4cf55f05235f4efe78bcfeb5a7704fb75c16b426a5de2fc1e6b7b8545b"},
+    {file = "moto-4.1.13-py2.py3-none-any.whl", hash = "sha256:9650d05d89b6f97043695548fbc0d8fb293f4177daaebbcee00bb0d171367f1a"},
+    {file = "moto-4.1.13.tar.gz", hash = "sha256:dd3e2ad920ab8b058c4f62fa7c195b788bd1f018cc701a1868ff5d5c4de6ed47"},
 ]
 
 [package.dependencies]
@@ -2521,41 +2621,6 @@ files = [
 [package.dependencies]
 ipython = "*"
 
-[[package]]
-name = "nbclassic"
-version = "1.0.0"
-description = "Jupyter Notebook as a Jupyter Server extension."
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "nbclassic-1.0.0-py3-none-any.whl", hash = "sha256:f99e4769b4750076cd4235c044b61232110733322384a94a63791d2e7beacc66"},
-    {file = "nbclassic-1.0.0.tar.gz", hash = "sha256:0ae11eb2319455d805596bf320336cda9554b41d99ab9a3c31bf8180bffa30e3"},
-]
-
-[package.dependencies]
-argon2-cffi = "*"
-ipykernel = "*"
-ipython-genutils = "*"
-jinja2 = "*"
-jupyter-client = ">=6.1.1"
-jupyter-core = ">=4.6.1"
-jupyter-server = ">=1.8"
-nbconvert = ">=5"
-nbformat = "*"
-nest-asyncio = ">=1.5"
-notebook-shim = ">=0.2.3"
-prometheus-client = "*"
-pyzmq = ">=17"
-Send2Trash = ">=1.8.0"
-terminado = ">=0.8.3"
-tornado = ">=6.1"
-traitlets = ">=4.2.1"
-
-[package.extras]
-docs = ["myst-parser", "nbsphinx", "sphinx", "sphinx-rtd-theme", "sphinxcontrib-github-alt"]
-json-logging = ["json-logging"]
-test = ["coverage", "nbval", "pytest", "pytest-cov", "pytest-jupyter", "pytest-playwright", "pytest-tornasync", "requests", "requests-unixsocket", "testpath"]
-
 [[package]]
 name = "nbclient"
 version = "0.8.0"
@@ -2580,13 +2645,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.6.0"
+version = "7.7.3"
 description = "Converting Jupyter Notebooks"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "nbconvert-7.6.0-py3-none-any.whl", hash = "sha256:5a445c6794b0791984bc5436608fe2c066cb43c83920c7bc91bde3b765e9a264"},
-    {file = "nbconvert-7.6.0.tar.gz", hash = "sha256:24fcf27efdef2b51d7f090cc5ce5a9b178766a55be513c4ebab08c91899ab550"},
+    {file = "nbconvert-7.7.3-py3-none-any.whl", hash = "sha256:3022adadff3f86578a47fab7c2228bb3ca9c56a24345642a22f917f6168b48fc"},
+    {file = "nbconvert-7.7.3.tar.gz", hash = "sha256:4a5996bf5f3cd16aa0431897ba1aa4c64842c2079f434b3dc6b8c4b252ef3355"},
 ]
 
 [package.dependencies]
@@ -2613,18 +2678,18 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["ipykernel", "ipywidgets (>=7)", "pre-commit", "pytest", "pytest-dependency"]
-webpdf = ["pyppeteer (>=1,<1.1)"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pre-commit", "pytest", "pytest-dependency"]
+webpdf = ["playwright"]
 
 [[package]]
 name = "nbformat"
-version = "5.9.0"
+version = "5.9.1"
 description = "The Jupyter Notebook format"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "nbformat-5.9.0-py3-none-any.whl", hash = "sha256:8c8fa16d6d05062c26177754bfbfac22de644888e2ef69d27ad2a334cf2576e5"},
-    {file = "nbformat-5.9.0.tar.gz", hash = "sha256:e98ebb6120c3efbafdee2a40af2a140cadee90bb06dd69a2a63d9551fcc7f976"},
+    {file = "nbformat-5.9.1-py3-none-any.whl", hash = "sha256:b7968ebf4811178a4108ee837eae1442e3f054132100f0359219e9ed1ce3ca45"},
+    {file = "nbformat-5.9.1.tar.gz", hash = "sha256:3a7f52d040639cbd8a3890218c8b0ffb93211588c57446c90095e32ba5881b5d"},
 ]
 
 [package.dependencies]
@@ -2682,37 +2747,26 @@ setuptools = "*"
 
 [[package]]
 name = "notebook"
-version = "6.5.4"
-description = "A web-based notebook environment for interactive computing"
+version = "7.0.0"
+description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "notebook-6.5.4-py3-none-any.whl", hash = "sha256:dd17e78aefe64c768737b32bf171c1c766666a21cc79a44d37a1700771cab56f"},
-    {file = "notebook-6.5.4.tar.gz", hash = "sha256:517209568bd47261e2def27a140e97d49070602eea0d226a696f42a7f16c9a4e"},
+    {file = "notebook-7.0.0-py3-none-any.whl", hash = "sha256:71b4e695e658763a2766613176491854708fb46fbe7664bf5e494deeeab92d60"},
+    {file = "notebook-7.0.0.tar.gz", hash = "sha256:38b55e6939df0ba73b53212c3b234e41102f1789e0158606cedaebf00abef6c8"},
 ]
 
 [package.dependencies]
-argon2-cffi = "*"
-ipykernel = "*"
-ipython-genutils = "*"
-jinja2 = "*"
-jupyter-client = ">=5.3.4"
-jupyter-core = ">=4.6.1"
-nbclassic = ">=0.4.7"
-nbconvert = ">=5"
-nbformat = "*"
-nest-asyncio = ">=1.5"
-prometheus-client = "*"
-pyzmq = ">=17"
-Send2Trash = ">=1.8.0"
-terminado = ">=0.8.3"
-tornado = ">=6.1"
-traitlets = ">=4.2.1"
+jupyter-server = ">=2.4.0,<3"
+jupyterlab = ">=4.0.2,<5"
+jupyterlab-server = ">=2.22.1,<3"
+notebook-shim = ">=0.2,<0.3"
+tornado = ">=6.2.0"
 
 [package.extras]
-docs = ["myst-parser", "nbsphinx", "sphinx", "sphinx-rtd-theme", "sphinxcontrib-github-alt"]
-json-logging = ["json-logging"]
-test = ["coverage", "nbval", "pytest", "pytest-cov", "requests", "requests-unixsocket", "selenium (==4.1.5)", "testpath"]
+dev = ["hatch", "pre-commit"]
+docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.22.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
 
 [[package]]
 name = "notebook-shim"
@@ -2733,36 +2787,36 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numpy"
-version = "1.25.0"
+version = "1.25.1"
 description = "Fundamental package for array computing in Python"
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "ruff-0.0.280-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2e7c15828d09f90e97bea8feefcd2907e8c8ce3a1f959c99f9b4b3469679f33c"},
+    {file = "ruff-0.0.280-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:2dae8f2d9c44c5c49af01733c2f7956f808db682a4193180dedb29dd718d7bbe"},
+    {file = "ruff-0.0.280-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:5f972567163a20fb8c2d6afc60c2ea5ef8b68d69505760a8bd0377de8984b4f6"},
+    {file = "ruff-0.0.280-py3-none-musllinux_1_2_i686.whl", hash = "sha256:8ffa7347ad11643f29de100977c055e47c988cd6d9f5f5ff83027600b11b9189"},
+    {file = "ruff-0.0.280-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:7a37dab70114671d273f203268f6c3366c035fe0c8056614069e90a65e614bfc"},
+    {file = "ruff-0.0.280-py3-none-win32.whl", hash = "sha256:7784e3606352fcfb193f3cd22b2e2117c444cb879ef6609ec69deabd662b0763"},
+    {file = "ruff-0.0.280-py3-none-win_amd64.whl", hash = "sha256:4a7d52457b5dfcd3ab24b0b38eefaead8e2dca62b4fbf10de4cd0938cf20ce30"},
+    {file = "ruff-0.0.280-py3-none-win_arm64.whl", hash = "sha256:b7de5b8689575918e130e4384ed9f539ce91d067c0a332aedef6ca7188adac2d"},
+    {file = "ruff-0.0.280.tar.gz", hash = "sha256:581c43e4ac5e5a7117ad7da2120d960a4a99e68ec4021ec3cd47fe1cf78f8380"},
 ]
 
 [[package]]
@@ -4091,13 +4166,13 @@ test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
 
 [[package]]
 name = "threadpoolctl"
-version = "3.1.0"
+version = "3.2.0"
 description = "threadpoolctl"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "threadpoolctl-3.1.0-py3-none-any.whl", hash = "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b"},
-    {file = "threadpoolctl-3.1.0.tar.gz", hash = "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"},
+    {file = "threadpoolctl-3.2.0-py3-none-any.whl", hash = "sha256:2b7818516e423bdaebb97c723f86a7c6b0a83d3f3b0970328d66f4d9104dc032"},
+    {file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
 ]
 
 [[package]]
@@ -4181,12 +4256,12 @@ files = [
 
 [[package]]
 name = "torchmetrics"
-version = "1.0.0"
+version = "1.0.1"
 description = "PyTorch native Metrics"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "torchmetrics-1.0.0-py3-none-any.whl", hash = "sha256:39bffd1f1746c38f7b0a6d58d632ce72287708ba55762bd3b7e48bee83e2e5f7"},
+    {file = "torchmetrics-1.0.1-py3-none-any.whl", hash = "sha256:5278ebdf4ecc168d88d87d3f02045ceee6a4a4ae24d8bf09d616ab67441dde0a"},
 ]
 
 [package.dependencies]
@@ -4196,13 +4271,13 @@ packaging = "*"
 torch = ">=1.8.1"
 
 [package.extras]
-all = ["SciencePlots (>=2.0.0)", "lpips (<=0.1.4)", "matplotlib (>=3.2.0)", "mypy (==1.4.1)", "nltk (>=3.6)", "pycocotools (>2.0.0)", "pystoi (<=0.3.3)", "regex (>=2021.9.24)", "scipy (>1.0.0)", "torch-fidelity (<=0.3.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
-audio = ["pystoi (<=0.3.3)", "torchaudio (>=0.10.0)"]
+all = ["SciencePlots (>=2.0.0)", "lpips (<=0.1.4)", "matplotlib (>=3.2.0)", "mypy (==1.4.1)", "nltk (>=3.6)", "pycocotools (>2.0.0)", "pystoi (>=0.3.0)", "regex (>=2021.9.24)", "scipy (>1.0.0)", "torch-fidelity (<=0.3.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
+audio = ["pystoi (>=0.3.0)", "torchaudio (>=0.10.0)"]
 detection = ["pycocotools (>2.0.0)", "torchvision (>=0.8)"]
-dev = ["SciencePlots (>=2.0.0)", "bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.2.7)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "fire (<=0.5.0)", "huggingface-hub (<0.16)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "lpips (<=0.1.4)", "matplotlib (>=3.2.0)", "mir-eval (>=0.6)", "mypy (==1.4.1)", "netcal (>1.0.0)", "nltk (>=3.6)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "psutil (<=5.9.5)", "pycocotools (>2.0.0)", "pystoi (<=0.3.3)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==0.13.0)", "pytest-rerunfailures (==11.1.2)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "regex (>=2021.9.24)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)", "torch-fidelity (<=0.3.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>4.4.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
+dev = ["SciencePlots (>=2.0.0)", "bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.2.7)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "fire (<=0.5.0)", "huggingface-hub (<0.16)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "lpips (<=0.1.4)", "matplotlib (>=3.2.0)", "mir-eval (>=0.6)", "mypy (==1.4.1)", "netcal (>1.0.0)", "nltk (>=3.6)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "psutil (<=5.9.5)", "pycocotools (>2.0.0)", "pystoi (>=0.3.0)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==0.13.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "regex (>=2021.9.24)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)", "torch-fidelity (<=0.3.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>4.4.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
 image = ["lpips (<=0.1.4)", "scipy (>1.0.0)", "torch-fidelity (<=0.3.0)", "torchvision (>=0.8)"]
 multimodal = ["transformers (>=4.10.0)"]
-test = ["bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.2.7)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "fire (<=0.5.0)", "huggingface-hub (<0.16)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "mir-eval (>=0.6)", "netcal (>1.0.0)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "psutil (<=5.9.5)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==0.13.0)", "pytest-rerunfailures (==11.1.2)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)", "transformers (>4.4.0)"]
+test = ["bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.2.7)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "fire (<=0.5.0)", "huggingface-hub (<0.16)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "mir-eval (>=0.6)", "netcal (>1.0.0)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "psutil (<=5.9.5)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==0.13.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)", "transformers (>4.4.0)"]
 text = ["nltk (>=3.6)", "regex (>=2021.9.24)", "tqdm (>=4.41.0)"]
 typing = ["mypy (==1.4.1)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
 visual = ["SciencePlots (>=2.0.0)", "matplotlib (>=3.2.0)"]
@@ -4264,13 +4339,13 @@ test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
 
 [[package]]
 name = "types-pyyaml"
-version = "6.0.12.10"
+version = "6.0.12.11"
 description = "Typing stubs for PyYAML"
 optional = false
 python-versions = "*"
 files = [
-    {file = "types-PyYAML-6.0.12.10.tar.gz", hash = "sha256:ebab3d0700b946553724ae6ca636ea932c1b0868701d4af121630e78d695fc97"},
-    {file = "types_PyYAML-6.0.12.10-py3-none-any.whl", hash = "sha256:662fa444963eff9b68120d70cda1af5a5f2aa57900003c2006d7626450eaae5f"},
+    {file = "types-PyYAML-6.0.12.11.tar.gz", hash = "sha256:7d340b19ca28cddfdba438ee638cd4084bde213e501a3978738543e27094775b"},
+    {file = "types_PyYAML-6.0.12.11-py3-none-any.whl", hash = "sha256:a461508f3096d1d5810ec5ab95d7eeecb651f3a15b71959999988942063bf01d"},
 ]
 
 [[package]]
@@ -4327,23 +4402,23 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.23.1"
+version = "20.24.2"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.23.1-py3-none-any.whl", hash = "sha256:34da10f14fea9be20e0fd7f04aba9732f84e593dac291b757ce42e3368a39419"},
-    {file = "virtualenv-20.23.1.tar.gz", hash = "sha256:8ff19a38c1021c742148edc4f81cb43d7f8c6816d2ede2ab72af5b84c749ade1"},
+    {file = "virtualenv-20.24.2-py3-none-any.whl", hash = "sha256:43a3052be36080548bdee0b42919c88072037d50d56c28bd3f853cbe92b953ff"},
+    {file = "virtualenv-20.24.2.tar.gz", hash = "sha256:fd8a78f46f6b99a67b7ec5cf73f92357891a7b3a40fd97637c27f854aae3b9e0"},
 ]
 
 [package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.12,<4"
-platformdirs = ">=3.5.1,<4"
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<4"
 
 [package.extras]
 docs = ["furo (>=2023.5.20)", "proselint (>=0.13)", "sphinx (>=7.0.1)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezer (>=0.4.6)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.8)", "time-machine (>=2.9)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
 name = "wcwidth"
@@ -4526,18 +4601,18 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.15.0"
+version = "3.16.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
-    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+    {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
+    {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
 
 [extras]
 dynamodb = ["boto3"]
diff --git a/tests/models/test_threshold.py b/tests/models/test_threshold.py
index 05834685..d58d72f0 100644
--- a/tests/models/test_threshold.py
+++ b/tests/models/test_threshold.py
@@ -2,7 +2,13 @@
 
 import numpy as np
 
-from numalogic.models.threshold import StdDevThreshold, StaticThreshold, SigmoidThreshold
+from numalogic.models.threshold import (
+    StdDevThreshold,
+    StaticThreshold,
+    SigmoidThreshold,
+    MahalanobisThreshold,
+)
+from numalogic.tools.exceptions import ModelInitializationError
 
 
 class TestStdDevThreshold(unittest.TestCase):
@@ -23,6 +29,53 @@ def test_estimator_score(self):
         self.assertAlmostEqual(0.93317, np.mean(score), places=2)
 
 
+class TestMahalanobisThreshold(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls) -> None:
+        rng = np.random.default_rng(42)
+        cls.x_train = rng.normal(size=(100, 15))
+        cls.x_test = rng.normal(size=(30, 15))
+
+    def test_init(self):
+        clf = MahalanobisThreshold(max_outlier_prob=0.25)
+        clf.fit(self.x_train)
+        md = clf.mahalanobis(self.x_test)
+        self.assertTupleEqual((self.x_test.shape[0],), md.shape)
+        self.assertGreater(all(md), 0.0)
+        self.assertGreater(clf.threshold, 0.0)
+        self.assertEqual(clf.std_factor, 2.0)
+
+    def test_init_err(self):
+        with self.assertRaises(ValueError):
+            MahalanobisThreshold(max_outlier_prob=0.0)
+        with self.assertRaises(ValueError):
+            MahalanobisThreshold(max_outlier_prob=1.0)
+
+    def test_predict(self):
+        clf = MahalanobisThreshold()
+        clf.fit(self.x_train)
+        y = clf.predict(self.x_test)
+        self.assertTupleEqual(self.x_test.shape, y.shape)
+        self.assertEqual(np.max(y), 1)
+        self.assertEqual(np.min(y), 0)
+
+    def test_predict_err(self):
+        clf = MahalanobisThreshold()
+        with self.assertRaises(ModelInitializationError):
+            clf.predict(self.x_test)
+
+    def test_score_samples(self):
+        clf = MahalanobisThreshold()
+        clf.fit(self.x_train)
+        y = clf.score_samples(self.x_test)
+        self.assertTupleEqual(self.x_test.shape, y.shape)
+
+    def test_score_samples_err(self):
+        clf = MahalanobisThreshold()
+        with self.assertRaises(ModelInitializationError):
+            clf.score_samples(self.x_test)
+
+
 class TestStaticThreshold(unittest.TestCase):
     def setUp(self) -> None:
         self.x = np.arange(20).reshape(10, 2).astype(float)