docs: add new steps to website

docs/_quarto.yml

@@ -70,6 +70,9 @@ website:
             - reference/steps-imputation.qmd
             - reference/steps-encoding.qmd
             - reference/steps-standardization.qmd
+            - reference/steps-discretization.qmd
+            - reference/steps-feature-selection.qmd
+            - reference/steps-feature-engineering.qmd
             - reference/steps-temporal.qmd
             - reference/steps-other.qmd
 
@@ -151,6 +154,8 @@ quartodoc:
           contents:
             - OneHotEncode
             - CategoricalEncode
+            - CountEncode
+            - TargetEncode
 
         - kind: page
           path: steps-standardization
@@ -160,6 +165,30 @@ quartodoc:
           contents:
             - ScaleStandard
 
+        - kind: page
+          path: steps-discretization
+          summary:
+            name: Discretization
+            desc: Discretization of numeric columns
+          contents:
+            - DiscretizeKBins
+
+        - kind: page
+          path: steps-feature-selection
+          summary:
+            name: Feature Selection
+            desc: Selecting useful features for modeling
+          contents:
+            - ZeroVariance
+
+        - kind: page
+          path: steps-feature-engineering
+          summary:
+            name: Feature Engineering
+            desc: Generating new features
+          contents:
+            - PolynomialFeatures
+
         - kind: page
           path: steps-temporal
           summary:

ibisml/steps/discretize.py

@@ -44,13 +44,13 @@ class DiscretizeKBins(Step):
 
     Bin all numeric columns.
 
-    >>> step = ml.KBinsDiscretizer(ml.numeric(), n_bins=10)
+    >>> step = ml.DiscretizeKBins(ml.numeric(), n_bins=10)
     >>> step.fit_table(p, Metadata())
     >>> step.transform_table(p)
 
     Bin specific numeric columns.
 
-    >>> step = ml.KBinsDiscretizer(["bill_length_mm"], strategy="quantile")
+    >>> step = ml.DiscretizeKBins(["bill_length_mm"], strategy="quantile")
     >>> step.fit_table(p, Metadata())
     >>> step.transform_table(p)
     """

ibisml/steps/feature_engineering.py

@@ -29,11 +29,11 @@ class PolynomialFeatures(Step):
 
     Generate polynomial features for all numeric columns with a degree is 2.
 
-    >>> step = ml.PolynomialFeatures(ml.numeric(), 2)
+    >>> step = ml.PolynomialFeatures(ml.numeric(), degree=2)
 
     Generate polynomial features a specific set of columns.
 
-    >>> step = ml.PolynomialFeatures(["x", "y"], 2)
+    >>> step = ml.PolynomialFeatures(["x", "y"], degree=2)
     """
 
     def __init__(self, inputs: SelectionType, *, degree: int = 2):