0.14.14

diabetes

Author: bartzbeielstein

pyproject.toml

@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "spotpython"
-version = "0.14.13"
+version = "0.14.14"
 authors = [
   { name="T. Bartz-Beielstein", email="tbb@bartzundbartz.de" }
 ]

src/spotPython/data/diabetes.py

@@ -10,6 +10,21 @@ class Diabetes(Dataset):
     and six blood serum measurements were obtained for each of n = 442 diabetes patients,
     as well as the response of interest,
     a quantitative measure of disease progression one year after baseline.
+    Number of Instances: 442
+    Number of Attributes:
+    First 10 columns are numeric predictive values.
+    Target: Column 11 is a quantitative measure of disease progression one year after baseline.
+    Attribute Information:
+    * age age in years
+    * sex
+    * bmi body mass index
+    * bp average blood pressure
+    * s1 tc, total serum cholesterol
+    * s2 ldl, low-density lipoproteins
+    * s3 hdl, high-density lipoproteins
+    * s4 tch, total cholesterol / HDL
+    * s5 ltg, possibly log of serum triglycerides level
+    * s6 glu, blood sugar level
 
     Args:
         feature_type (torch.dtype): The data type of the features. Defaults to torch.float.
@@ -45,6 +60,7 @@ def __init__(
         self.feature_type = feature_type
         self.target_type = target_type
         self.train = train
+        self.names = self.get_names()
         self.data, self.targets = self._load_data()
 
     def _load_data(self) -> tuple:
@@ -122,3 +138,18 @@ def extra_repr(self) -> str:
         """
         split = "Train" if self.train else "Test"
         return f"Split: {split}"
+
+    def get_names(self) -> list:
+        """
+        Returns the names of the features.
+
+        Returns:
+            list: A list containing the names of the features.
+
+        Examples:
+            >>> from spotPython.data.diabetes import Diabetes
+                dataset = Diabetes()
+                print(dataset.get_names())
+                ["age", "sex", "bmi", "bp", "tc", "ldl", "hdl", "tch", "ltg", "glu"]
+        """
+        return ["age", "sex", "bmi", "bp", "tc", "ldl", "hdl", "tch", "ltg", "glu"]