[BUG] SAR needs to be modified due to a breaking change in spicy
### Description
<!--- Describe your issue/bug/request in detail -->
With scipy 1.10.1, the item similarity matrix is a dense matrix
```
print(type(model.item_similarity))
print(type(model.user_affinity))
print(type(model.item_similarity) == np.ndarray)
print(type(model.item_similarity) == scipy.sparse._csr.csr_matrix)
print(model.item_similarity.shape)
print(model.item_similarity)

<class 'numpy.ndarray'>
<class 'scipy.sparse._csr.csr_matrix'>
True
False
(1646, 1646)
[[1.         0.10650888 0.03076923 ... 0.         0.         0.        ]
 [0.10650888 1.         0.15104167 ... 0.         0.00729927 0.00729927]
 [0.03076923 0.15104167 1.         ... 0.         0.         0.01190476]
 ...
 [0.         0.         0.         ... 1.         0.         0.        ]
 [0.         0.00729927 0.         ... 0.         1.         0.        ]
 [0.         0.00729927 0.01190476 ... 0.         0.         1.        ]]
```

but with scipy 1.11.1 the item similarity matrix is sparse
```
print(type(model.item_similarity))
print(type(model.user_affinity))
type(model.item_similarity) == np.ndarray
type(model.item_similarity) == scipy.sparse._csr.csr_matrix
print(model.item_similarity.shape)
<class 'numpy.ndarray'>
<class 'scipy.sparse._csr.csr_matrix'>
()
```


### In which platform does it happen?
<!--- Describe the platform where the issue is happening (use a list if needed) -->
<!--- For example: -->
<!--- * Azure Data Science Virtual Machine. -->
<!--- * Azure Databricks.  -->
<!--- * Other platforms.  -->
Related to https://github.com/microsoft/recommenders/issues/1951

### How do we replicate the issue?
<!--- Please be specific as possible (use a list if needed). -->
<!--- For example: -->
<!--- * Create a conda environment for pyspark -->
<!--- * Run unit test `test_sar_pyspark.py` with `pytest -m 'spark'` -->
<!--- * ... -->

### Expected behavior (i.e. solution)
<!--- For example:  -->
<!--- * The tests for SAR PySpark should pass successfully. -->

### Other Comments
We found that the issue was that during a division in Jaccard, scipy change the type. We talked to the authors of scipy and they told us that they did a breaking change in 1.11.0 https://github.com/scipy/scipy/issues/18796#issuecomment-1619125257





diff --git a/setup.py b/setup.py
index 2be2b53f..3d5510b0 100644
--- a/setup.py
+++ b/setup.py
@@ -29,7 +29,7 @@ if HASH is not None:
 install_requires = [
     "numpy>=1.19",  # 1.19 required by tensorflow 2.6
     "pandas>1.0.3,<2",
-    "scipy>=1.0.0,<2,!=1.11.0,!=1.11.1",
+    "scipy>=1.0.0,<1.11.0", #FIXME: We limit <1.11.0 until #1954 is fixed
     "tqdm>=4.31.1,<5",
     "matplotlib>=2.2.2,<4",
     "scikit-learn>=0.22.1,<1.0.3",
['setup.py']