RHOAIENG-26843, RHOAIENG-26066 : chore(deps): bump scikit-learn from 1.2.2 to 1.5.1 in /jupyter/trustyai/ubi9-python-3.11 (opendatahub-io#1126)

* Chore(deps): bump scikit-learn in /jupyter/trustyai/ubi9-python-3.11

Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.2.2 to 1.5.1.
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.2.2...1.5.1)

---
updated-dependencies:
- dependency-name: scikit-learn
  dependency-version: 1.5.1
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>

* fixup, update Scikit-learn version to 1.5 in Jupyter trustyai notebook imagestream

* Update Pipfile.lock files by piplock-renewal.yaml action

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Jiri Daněk <[email protected]>
Co-authored-by: GitHub Actions <github-actions[bot]@users.noreply.github.com>

Author: 3 people

jupyter/trustyai/ubi9-python-3.11/Pipfile

@@ -29,7 +29,7 @@ matplotlib = "~=3.6.3" # Should be pinned down to this version in order to be co
 numpy = "~=1.24.1" # Should be pinned down to this version in order to be compatible with trustyai
 pandas = "~=1.5.3" # Should be pinned down to this version in order to be compatible with trustyai
 plotly = "~=6.0.0"
-scikit-learn = "~=1.2.1" # Should be pinned down to this version in order to be compatible with trustyai
+scikit-learn = "~=1.5.0" # Should be pinned down to this version in order to be compatible with trustyai
 scipy = "~=1.15.2"
 skl2onnx = "~=1.18.0"
 onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf

jupyter/trustyai/ubi9-python-3.11/Pipfile.lock

@@ -915,9 +915,9 @@ httpcore==1.0.9; python_version >= '3.8' \
 httpx==0.28.1; python_version >= '3.8' \
     --hash=sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc \
     --hash=sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad
-huggingface-hub==0.33.0; python_full_version >= '3.8.0' \
-    --hash=sha256:aa31f70d29439d00ff7a33837c03f1f9dd83971ce4e29ad664d63ffb17d3bb97 \
-    --hash=sha256:e8668875b40c68f9929150d99727d39e5ebb8a05a98e4191b908dc7ded9074b3
+huggingface-hub==0.33.1; python_full_version >= '3.8.0' \
+    --hash=sha256:589b634f979da3ea4b8bdb3d79f97f547840dc83715918daf0b64209c0844c7b \
+    --hash=sha256:ec8d7444628210c0ba27e968e3c4c973032d44dcea59ca0d78ef3f612196f095
 idna==3.10; python_version >= '3.6' \
     --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
     --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
@@ -2607,28 +2607,33 @@ safetensors==0.5.3; python_version >= '3.7' \
     --hash=sha256:cead1fa41fc54b1e61089fa57452e8834f798cb1dc7a09ba3524f1eb08e0317a \
     --hash=sha256:cfc0ec0846dcf6763b0ed3d1846ff36008c6e7290683b61616c4b040f6a54ace \
     --hash=sha256:df26da01aaac504334644e1b7642fa000bfec820e7cef83aeac4e355e03195ff
-scikit-learn==1.2.2; python_version >= '3.8' \
-    --hash=sha256:065e9673e24e0dc5113e2dd2b4ca30c9d8aa2fa90f4c0597241c93b63130d233 \
-    --hash=sha256:2dd3ffd3950e3d6c0c0ef9033a9b9b32d910c61bd06cb8206303fb4514b88a49 \
-    --hash=sha256:2e2642baa0ad1e8f8188917423dd73994bf25429f8893ddbe115be3ca3183584 \
-    --hash=sha256:44b47a305190c28dd8dd73fc9445f802b6ea716669cfc22ab1eb97b335d238b1 \
-    --hash=sha256:6477eed40dbce190f9f9e9d0d37e020815825b300121307942ec2110302b66a3 \
-    --hash=sha256:6fe83b676f407f00afa388dd1fdd49e5c6612e551ed84f3b1b182858f09e987d \
-    --hash=sha256:7d5312d9674bed14f73773d2acf15a3272639b981e60b72c9b190a0cffed5bad \
-    --hash=sha256:7f69313884e8eb311460cc2f28676d5e400bd929841a2c8eb8742ae78ebf7c20 \
-    --hash=sha256:8156db41e1c39c69aa2d8599ab7577af53e9e5e7a57b0504e116cc73c39138dd \
-    --hash=sha256:8429aea30ec24e7a8c7ed8a3fa6213adf3814a6efbea09e16e0a0c71e1a1a3d7 \
-    --hash=sha256:8b0670d4224a3c2d596fd572fb4fa673b2a0ccfb07152688ebd2ea0b8c61025c \
-    --hash=sha256:953236889928d104c2ef14027539f5f2609a47ebf716b8cbe4437e85dce42744 \
-    --hash=sha256:99cc01184e347de485bf253d19fcb3b1a3fb0ee4cea5ee3c43ec0cc429b6d29f \
-    --hash=sha256:9c710ff9f9936ba8a3b74a455ccf0dcf59b230caa1e9ba0223773c490cab1e51 \
-    --hash=sha256:ad66c3848c0a1ec13464b2a95d0a484fd5b02ce74268eaa7e0c697b904f31d6c \
-    --hash=sha256:bf036ea7ef66115e0d49655f16febfa547886deba20149555a41d28f56fd6d3c \
-    --hash=sha256:dfeaf8be72117eb61a164ea6fc8afb6dfe08c6f90365bde2dc16456e4bc8e45f \
-    --hash=sha256:e6e574db9914afcb4e11ade84fab084536a895ca60aadea3041e85b8ac963edb \
-    --hash=sha256:ea061bf0283bf9a9f36ea3c5d3231ba2176221bbd430abd2603b1c3b2ed85c89 \
-    --hash=sha256:fe0aa1a7029ed3e1dcbf4a5bc675aa3b1bc468d9012ecf6c6f081251ca47f590 \
-    --hash=sha256:fe175ee1dab589d2e1033657c5b6bec92a8a3b69103e3dd361b58014729975c3
+scikit-learn==1.5.2; python_version >= '3.9' \
+    --hash=sha256:03b6158efa3faaf1feea3faa884c840ebd61b6484167c711548fce208ea09445 \
+    --hash=sha256:178ddd0a5cb0044464fc1bfc4cca5b1833bfc7bb022d70b05db8530da4bb3dd3 \
+    --hash=sha256:1ff45e26928d3b4eb767a8f14a9a6efbf1cbff7c05d1fb0f95f211a89fd4f5de \
+    --hash=sha256:299406827fb9a4f862626d0fe6c122f5f87f8910b86fe5daa4c32dcd742139b6 \
+    --hash=sha256:2d4cad1119c77930b235579ad0dc25e65c917e756fe80cab96aa3b9428bd3fb0 \
+    --hash=sha256:394397841449853c2290a32050382edaec3da89e35b3e03d6cc966aebc6a8ae6 \
+    --hash=sha256:3a686885a4b3818d9e62904d91b57fa757fc2bed3e465c8b177be652f4dd37c8 \
+    --hash=sha256:3b923d119d65b7bd555c73be5423bf06c0105678ce7e1f558cb4b40b0a5502b1 \
+    --hash=sha256:3bed4909ba187aca80580fe2ef370d9180dcf18e621a27c4cf2ef10d279a7efe \
+    --hash=sha256:52788f48b5d8bca5c0736c175fa6bdaab2ef00a8f536cda698db61bd89c551c1 \
+    --hash=sha256:57cc1786cfd6bd118220a92ede80270132aa353647684efa385a74244a41e3b1 \
+    --hash=sha256:643964678f4b5fbdc95cbf8aec638acc7aa70f5f79ee2cdad1eec3df4ba6ead8 \
+    --hash=sha256:6c16d84a0d45e4894832b3c4d0bf73050939e21b99b01b6fd59cbb0cf39163b6 \
+    --hash=sha256:757c7d514ddb00ae249832fe87100d9c73c6ea91423802872d9e74970a0e40b9 \
+    --hash=sha256:8c412ccc2ad9bf3755915e3908e677b367ebc8d010acbb3f182814524f2e5540 \
+    --hash=sha256:b0768ad641981f5d3a198430a1d31c3e044ed2e8a6f22166b4d546a5116d7908 \
+    --hash=sha256:b4237ed7b3fdd0a4882792e68ef2545d5baa50aca3bb45aa7df468138ad8f94d \
+    --hash=sha256:b7b0f9a0b1040830d38c39b91b3a44e1b643f4b36e36567b80b7c6bd2202a27f \
+    --hash=sha256:c15b1ca23d7c5f33cc2cb0a0d6aaacf893792271cddff0edbd6a40e8319bc113 \
+    --hash=sha256:ca64b3089a6d9b9363cd3546f8978229dcbb737aceb2c12144ee3f70f95684b7 \
+    --hash=sha256:e9a702e2de732bbb20d3bad29ebd77fc05a6b427dc49964300340e4c9328b3f5 \
+    --hash=sha256:f60021ec1574e56632be2a36b946f8143bf4e5e6af4a06d85281adc22938e0dd \
+    --hash=sha256:f7284ade780084d94505632241bf78c44ab3b6f1e8ccab3d2af58e0e950f9c12 \
+    --hash=sha256:f763897fe92d0e903aa4847b0aec0e68cadfff77e8a0687cabd946c89d17e675 \
+    --hash=sha256:f8b0ccd4a902836493e026c03256e8b206656f91fbcc4fde28c57a5b752561f1 \
+    --hash=sha256:f932a02c3f4956dfb981391ab24bda1dbd90fe3d628e4b42caef3e041c67707a
 scipy==1.15.3; python_version >= '3.10' \
     --hash=sha256:05dc6abcd105e1a29f95eada46d4a3f251743cfd7d3ae8ddb4088047f24ea477 \
     --hash=sha256:06efcba926324df1696931a57a176c80848ccd67ce6ad020c810736bfd58eb1c \

jupyter/trustyai/ubi9-python-3.11/requirements.txt

@@ -36,7 +36,7 @@ spec:
             {"name": "Matplotlib", "version": "3.6"},
             {"name": "Numpy", "version": "1.24"},
             {"name": "Pandas", "version": "1.5"},
-            {"name": "Scikit-learn", "version": "1.2"},
+            {"name": "Scikit-learn", "version": "1.5"},
             {"name": "Scipy", "version": "1.15"},
             {"name": "Odh-Elyra", "version": "4.2"},
             {"name": "PyMongo", "version": "4.11"},