Add Matthews Correlation Coefficient (#561)

* Add Matthews Correlation Coefficient (MCC) metric

* Reorder arguments in _multilabel_mcc_reference function

* update linux version for code check

* revert ubuntu version change & update action versions

* use torch instead of dlpack to convert tensors to numpy

* update numpy conversion methods

* set dtype for multilabel test inputs

* fix doctest error

* update implementation of multilabel confusion matrix

* revert implementation update & add print statements for debugging

* fix tests

* use float64 for internal computations

* Refactor test files and remove debug print statement

* Fix data type in Matthews correlation coefficient calculation

* Update dtype in _mcc_reduce function

* Fix NaN handling in confusion matrix computation

* use epsilon to check `denom` to avoid precision issues

---------

Signed-off-by: Amrit Krishnan <amrit110@gmail.com>
Co-authored-by: Amrit Krishnan <amrit110@gmail.com>

cyclops/evaluate/metrics/experimental/__init__.py

@@ -29,6 +29,11 @@
 )
 from cyclops.evaluate.metrics.experimental.mae import MeanAbsoluteError
 from cyclops.evaluate.metrics.experimental.mape import MeanAbsolutePercentageError
+from cyclops.evaluate.metrics.experimental.matthews_corr_coef import (
+    BinaryMCC,
+    MulticlassMCC,
+    MultilabelMCC,
+)
 from cyclops.evaluate.metrics.experimental.metric_dict import MetricDict
 from cyclops.evaluate.metrics.experimental.mse import MeanSquaredError
 from cyclops.evaluate.metrics.experimental.negative_predictive_value import (

cyclops/evaluate/metrics/experimental/confusion_matrix.py

@@ -1,4 +1,5 @@
 """Confusion matrix."""
+
 from types import ModuleType
 from typing import Any, Optional, Tuple, Union
 

cyclops/evaluate/metrics/experimental/functional/__init__.py

@@ -31,6 +31,11 @@
 from cyclops.evaluate.metrics.experimental.functional.mape import (
     mean_absolute_percentage_error,
 )
+from cyclops.evaluate.metrics.experimental.functional.matthews_corr_coef import (
+    binary_mcc,
+    multiclass_mcc,
+    multilabel_mcc,
+)
 from cyclops.evaluate.metrics.experimental.functional.mse import mean_squared_error
 from cyclops.evaluate.metrics.experimental.functional.negative_predictive_value import (
     binary_npv,

cyclops/evaluate/metrics/experimental/functional/confusion_matrix.py

@@ -1,5 +1,7 @@
 """Functions for computing the confusion matrix for classification tasks."""
+
 # mypy: disable-error-code="no-any-return"
+import warnings
 from types import ModuleType
 from typing import Literal, Optional, Tuple, Union
 
@@ -40,6 +42,16 @@ def _normalize_confusion_matrix(
     if normalize == "all":
         return safe_divide(confmat, xp.sum(confmat, axis=(-1, -2), keepdims=True))
 
+    nan_elements = int(0 or apc.size(confmat[xp.isnan(confmat)]))
+    if nan_elements:
+        confmat[xp.isnan(confmat)] = 0
+        warnings.warn(
+            f"Encountered {nan_elements} NaN elements in the confusion matrix. "
+            "These elements were replaced with 0.",
+            category=RuntimeWarning,
+            stacklevel=1,
+        )
+
     return confmat