[BUG] Fix Laplace energy_self calculation and docstring typos (#720)

#### Reference Issues/PRs

Fixes #719 

#### What does this implement/fix? Explain your changes.

1. **Bug fix in `Laplace._energy_self`**: The 1.5 multiplier for
self-energy was incorrectly placed inside the array dimension check,
causing scalar Laplace distributions to return wrong energy values.
Moved the multiplier to apply unconditionally before the dimension
check.

2. **Docstring convention fixes**: Changed `Parameter` → `Parameters`
and `Return` → `Returns` to follow NumPy docstring conventions in:
   - exponential.py
   - _base.py
   - evaluate.py
   - _show_versions.py

3. **Input validation in `evaluate()`**: Added a check that `X` and `y`
have the same length, providing a clear error message instead of cryptic
failures downstream.

#### Does your contribution introduce a new dependency? If yes, which
one?

No.

#### What should a reviewer concentrate their feedback on?

- Verify the mathematical correctness of the Laplace energy fix
- Confirm the input validation message is appropriate

Author: Ashish-Kumar-Dash

.all-contributorsrc

@@ -61,10 +61,10 @@
       "avatar_url": "https://avatars.githubusercontent.com/u/2273226?v=4",
       "profile": "https://github.com/iwitaly",
       "contributions": [
-          "code",
-          "doc",
-          "maintenance",
-          "review"
+        "code",
+        "doc",
+        "maintenance",
+        "review"
       ]
     },
     {
@@ -73,8 +73,8 @@
       "avatar_url": "https://avatars.githubusercontent.com/u/39331844?v=4",
       "profile": "https://github.com/yarnabrina",
       "contributions": [
-          "code",
-          "maintenance"
+        "code",
+        "maintenance"
       ]
     },
     {
@@ -127,8 +127,8 @@
       "avatar_url": "https://avatars.githubusercontent.com/u/120820143?s=400&v=4",
       "profile": "https://github.com/ShreeshaM07",
       "contributions": [
-          "code",
-          "doc"
+        "code",
+        "doc"
       ]
     },
     {
@@ -212,15 +212,24 @@
       "profile": "https://github.com/tingiskhan",
       "contributions": [
         "code",
-        "bug",
+        "bug"
       ]
     },
     {
       "login": "joshdunnlime",
       "name": "Josh Dunn",
       "profile": "https://github.com/joshdunnlime",
+      "contributions": [
+        "code"
+      ]
+    },
+    {
+      "login": "Ashish-Kumar-Dash",
+      "name": "Ashish Kumar Dash",
+      "profile": "https://github.com/Ashish-Kumar-Dash",
       "contributions": [
         "code",
+        "bug"
       ]
     }
   ]

skpro/benchmarking/evaluate.py

@@ -194,8 +194,11 @@ def evaluate(
             "but dask is not present in the python environment"
         )
 
-    # todo: input checks and coercions
-    # cv = check_cv(cv, enforce_start_with_window=True)
+    if len(X) != len(y):
+        raise ValueError(
+            f"X and y must have the same number of rows, "
+            f"but found len(X)={len(X)} and len(y)={len(y)}"
+        )
 
     scoring = _check_scores(scoring)
 
@@ -408,8 +411,8 @@ def _check_scores(metrics):
     ----------
     metrics : skpro accepted metrics object or a list of them or None
 
-    Return
-    ------
+    Returns
+    -------
     metrics_type : Dict
         The key is metric types and its value is a list of its corresponding metrics.
     """

skpro/distributions/exponential.py

@@ -22,8 +22,8 @@ class Exponential(_ScipyAdapter):
 
     The rate :math:`\lambda` is represented by the parameter ``rate``,
 
-    Parameter
-    ---------
+    Parameters
+    ----------
     rate : float or array of float (1D or 2D)
         rate of the distribution
         rate = 1/scale

skpro/distributions/laplace.py

@@ -69,9 +69,9 @@ def _energy_self(self):
         2D np.ndarray, same shape as ``self``
             energy values w.r.t. the given points
         """
-        energy_arr = self._bc_params["scale"]
+        energy_arr = self._bc_params["scale"] * 1.5
         if energy_arr.ndim > 0:
-            energy_arr = np.sum(energy_arr, axis=1) * 1.5
+            energy_arr = np.sum(energy_arr, axis=1)
         return energy_arr
 
     def _energy_x(self, x):

skpro/regression/base/_base.py

@@ -933,8 +933,8 @@ def _get_columns(self, method="predict", **kwargs):
         Primarily used as helper for probabilistic predict-like methods.
         Assumes that _check_X_y has been called, and self._y_metadata set.
 
-        Parameter
-        ---------
+        Parameters
+        ----------
         method : str, optional (default="predict")
             method for which to return column names
             one of "predict", "predict_interval", "predict_quantiles", "predict_var"

skpro/utils/_maint/_show_versions.py

@@ -17,8 +17,8 @@
 def _get_sys_info():
     """System information.
 
-    Return
-    ------
+    Returns
+    -------
     sys_info : dict
         system and Python version information
     """