restore tutorials

MLBazaar · Nov 15, 2024 · 298ee43 · 298ee43
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Showing 6 changed files with 11 additions and 11 deletions.
diff --git a/README.md b/README.md
@@ -99,7 +99,7 @@ X_train, X_test, y_train, y_test = train_test_split(dataset, label, stratify=lab
 primitives = [
     'mlprimitives.custom.preprocessing.ClassEncoder',
     'mlprimitives.custom.feature_extraction.CategoricalEncoder',
-    # 'sklearn.impute.SimpleImputer',
+    'sklearn.impute.SimpleImputer',
     'xgboost.XGBClassifier',
     'mlprimitives.custom.preprocessing.ClassDecoder'
 ]

diff --git a/examples/tutorials/1. Using and MLPipeline.ipynb b/examples/tutorials/1. Using and MLPipeline.ipynb
@@ -361,7 +361,7 @@
     "primitives = [\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder',\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder',\n",
-    "    # 'sklearn.impute.SimpleImputer',\n",
+    "    'sklearn.impute.SimpleImputer',\n",
     "    'xgboost.XGBClassifier',\n",
     "    'mlprimitives.custom.preprocessing.ClassDecoder'\n",
     "]\n",

diff --git a/examples/tutorials/3. Setting MLPipeline Hyperparameters.ipynb b/examples/tutorials/3. Setting MLPipeline Hyperparameters.ipynb
@@ -54,7 +54,7 @@
     "primitives = [\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder',\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder',\n",
-    "    # 'sklearn.impute.SimpleImputer',\n",
+    "    'sklearn.impute.SimpleImputer',\n",
     "    'xgboost.XGBClassifier',\n",
     "    'mlprimitives.custom.preprocessing.ClassDecoder'\n",
     "]\n",

diff --git a/examples/tutorials/4. Saving and Loading a Pipeline.ipynb b/examples/tutorials/4. Saving and Loading a Pipeline.ipynb
@@ -60,7 +60,7 @@
     "primitives = [\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder',\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder',\n",
-    "    # 'sklearn.impute.SimpleImputer',\n",
+    "    'sklearn.impute.SimpleImputer',\n",
     "    'xgboost.XGBClassifier',\n",
     "    'mlprimitives.custom.preprocessing.ClassDecoder'\n",
     "]\n",

diff --git a/examples/tutorials/5. Partial execution and pipeline debugging.ipynb b/examples/tutorials/5. Partial execution and pipeline debugging.ipynb
@@ -275,7 +275,7 @@
     "primitives = [\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder',\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder',\n",
-    "    # 'sklearn.impute.SimpleImputer',\n",
+    "    'sklearn.impute.SimpleImputer',\n",
     "    'xgboost.XGBClassifier',\n",
     "    'mlprimitives.custom.preprocessing.ClassDecoder'\n",
     "]\n",

diff --git a/examples/tutorials/6. Flexible outputs specification.ipynb b/examples/tutorials/6. Flexible outputs specification.ipynb
@@ -62,7 +62,7 @@
     "primitives = [\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder',\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder',\n",
-    "    # 'sklearn.impute.SimpleImputer',\n",
+    "    'sklearn.impute.SimpleImputer',\n",
     "    'xgboost.XGBClassifier',\n",
     "    'mlprimitives.custom.preprocessing.ClassDecoder'\n",
     "]\n",
@@ -432,11 +432,11 @@
    ],
    "source": [
     "output_spec = [\n",
-    "    # 'sklearn.impute.SimpleImputer#1.X',\n",
+    "    'sklearn.impute.SimpleImputer#1.X',\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder#1.y',\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder#1.classes',\n",
     "]\n",
-    "y, classes = pipeline.fit(X_train, y_train, output_=output_spec)"
+    "X, y, classes = pipeline.fit(X_train, y_train, output_=output_spec)"
    ]
   },
   {
@@ -463,11 +463,11 @@
    "source": [
     "output_spec = [\n",
     "    'mlprimitives.custom.feature_extraction.CategoricalEncoder#1.X',\n",
-    "    # 'sklearn.impute.SimpleImputer#1.X',\n",
+    "    'sklearn.impute.SimpleImputer#1.X',\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder#1.y',\n",
     "    'mlprimitives.custom.preprocessing.ClassEncoder#1.classes',\n",
     "]\n",
-    "X_1, y, classes = pipeline.fit(X_train, y_train, output_=output_spec)"
+    "X_1, X_2, y, classes = pipeline.fit(X_train, y_train, output_=output_spec)"
    ]
   },
   {
@@ -507,7 +507,7 @@
     }
    ],
    "source": [
-    "X_1.shape"
+    "X_2.shape"
    ]
   }
  ],