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README.md

@@ -1,3 +1,26 @@
 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- post_operative
+- tabular_classification
+- binary_classification
+- multiclass_classification
+pretty_name: Page Blocks
+size_categories:
+- 1K<n<10K
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- post_operative
+- post_operative_binary
 ---
+# Post Operative
+The [PostOperative dataset](https://archive-beta.ics.uci.edu/dataset/82/post+operative+patient) from the [UCI repository](https://archive-beta.ics.uci.edu/).
+Should the patient be discharged from the hospital?
+
+# Configurations and tasks
+| **Configuration** | **Task**                  |
+|-------------------|---------------------------|
+| post_operative       | Multiclass classification |
+| post_operative_binary| Binary classification     |

post-operative.data

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+internal_temperature,surface_temperature,oxigen_saturation,blood_pressure,surface_temperature_stability,internal_temperature_stability,blood_pressure_stability,perceived_comfort,decision
+mid,low,excellent,mid,stable,stable,stable,15,0
+mid,high,excellent,high,stable,stable,stable,10,1
+high,low,excellent,high,stable,stable,mod-stable,10,0
+mid,low,good,high,stable,unstable,mod-stable,15,A 
+mid,mid,excellent,high,stable,stable,stable,10,0
+high,low,good,mid,stable,stable,unstable,15,1
+mid,low,excellent,high,stable,stable,mod-stable,05,1
+high,mid,excellent,mid,unstable,unstable,stable,10,1
+mid,high,good,mid,stable,stable,stable,10,1
+mid,low,excellent,mid,unstable,stable,mod-stable,10,1
+mid,mid,good,mid,stable,stable,stable,15,0
+mid,low,good,high,stable,stable,mod-stable,10,0
+high,high,excellent,high,unstable,stable,unstable,15,0
+mid,high,good,mid,unstable,stable,mod-stable,10,0
+mid,low,good,high,unstable,unstable,stable,15,1
+high,high,excellent,high,unstable,stable,unstable,10,0
+low,high,good,high,unstable,stable,mod-stable,15,0
+mid,low,good,high,unstable,stable,stable,10,0
+mid,high,good,mid,unstable,stable,unstable,15,0
+mid,mid,good,mid,stable,stable,stable,10,0
+low,high,good,mid,unstable,stable,stable,15,0
+low,mid,excellent,high,unstable,stable,unstable,10,1
+mid,mid,good,mid,unstable,stable,unstable,15,0
+mid,mid,good,mid,unstable,stable,stable,10,0
+high,high,good,mid,stable,stable,mod-stable,10,0
+low,mid,good,mid,unstable,stable,stable,10,0
+high,mid,good,low,stable,stable,mod-stable,10,0
+low,mid,excellent,high,stable,stable,mod-stable,10,0
+mid,mid,excellent,mid,stable,stable,unstable,15,0
+mid,mid,good,mid,unstable,stable,unstable,10,1
+mid,mid,good,high,unstable,stable,stable,10,0
+low,low,good,mid,unstable,stable,unstable,10,0
+mid,mid,excellent,high,unstable,stable,mod-stable,10,0
+mid,low,good,mid,stable,stable,stable,10,0
+low,mid,excellent,high,stable,stable,mod-stable,10,0
+mid,mid,good,mid,stable,stable,stable,10,0
+low,mid,excellent,mid,stable,stable,stable,10,1
+low,low,good,mid,unstable,stable,unstable,10,1
+low,low,good,mid,stable,stable,stable,07,1
+mid,mid,good,high,unstable,stable,mod-stable,10,0
+low,low,good,mid,unstable,stable,stable,10,0
+low,mid,good,mid,stable,stable,stable,15,1
+high,high,good,high,unstable,stable,stable,15,1
+mid,mid,good,mid,stable,stable,stable,10,1
+low,low,excellent,mid,stable,stable,stable,10,0
+low,mid,good,mid,unstable,stable,stable,10,1
+low,mid,good,high,unstable,stable,stable,?,2
+mid,mid,excellent,mid,unstable,stable,stable,10,0
+high,high,excellent,high,stable,stable,unstable,?,0
+mid,high,good,low,unstable,stable,stable,10,0
+mid,high,good,mid,unstable,mod-stable,mod-stable,10,0
+low,high,excellent,mid,unstable,stable,stable,10,0
+mid,low,excellent,high,unstable,stable,unstable,10,0
+mid,mid,good,mid,unstable,stable,mod-stable,10,1
+high,high,excellent,mid,unstable,stable,mod-stable,10,0
+mid,mid,good,mid,unstable,stable,stable,15,0
+high,mid,good,high,stable,stable,unstable,15,0
+mid,low,good,high,unstable,stable,mod-stable,10,0
+low,low,good,high,stable,stable,stable,10,0
+mid,high,good,mid,stable,stable,mod-stable,10,0
+mid,high,good,mid,unstable,stable,unstable,10,0
+mid,low,excellent,high,stable,stable,stable,10,0
+mid,mid,good,mid,stable,stable,unstable,10,0
+mid,low,excellent,mid,stable,stable,unstable,10,1
+high,mid,excellent,mid,unstable,unstable,unstable,10,0
+mid,mid,good,high,stable,stable,stable,10,1
+mid,low,excellent,mid,unstable,stable,stable,10,0
+mid,mid,excellent,mid,unstable,stable,stable,10,0
+mid,mid,excellent,high,stable,stable,stable,10,0
+mid,mid,excellent,low,stable,stable,stable,10,0
+mid,low,excellent,mid,unstable,unstable,unstable,?,0
+low,low,excellent,mid,stable,stable,stable,10,0
+mid,mid,excellent,mid,stable,stable,mod-stable,10,1
+mid,mid,excellent,high,stable,stable,stable,10,0
+mid,low,excellent,high,stable,stable,mod-stable,10,0
+low,mid,good,mid,stable,stable,unstable,10,0
+mid,mid,excellent,mid,stable,stable,mod-stable,10,0
+mid,mid,excellent,mid,stable,stable,unstable,10,0
+mid,mid,excellent,mid,unstable,unstable,stable,10,1
+mid,mid,good,high,stable,stable,stable,10,0
+mid,mid,excellent,mid,stable,stable,stable,15,0
+mid,mid,excellent,mid,stable,stable,stable,10,1
+mid,low,good,mid,stable,stable,unstable,10,2
+high,mid,excellent,mid,unstable,stable,unstable,05,0
+mid,mid,excellent,mid,stable,stable,unstable,10,0
+mid,mid,excellent,mid,unstable,stable,stable,10,0
+mid,mid,excellent,mid,unstable,stable,stable,15,1
+mid,mid,good,mid,unstable,stable,stable,15,0
+mid,mid,excellent,mid,unstable,stable,stable,10,0
+mid,mid,good,mid,unstable,stable,stable,15,1

post_operative.py

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+"""PostOperative Dataset"""
+
+from typing import List
+from functools import partial
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+
+_ENCODING_DICS = {
+}
+
+DESCRIPTION = "PostOperative dataset."
+_HOMEPAGE = "https://archive-beta.ics.uci.edu/dataset/78/page+blocks+classification"
+_URLS = ("https://archive-beta.ics.uci.edu/dataset/78/page+blocks+classification")
+_CITATION = """
+@misc{misc_post-operative_patient_82,
+  author       = {Summers,Sharon & Woolery,Linda},
+  title        = {{Post-Operative Patient}},
+  year         = {1993},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \\url{10.24432/C5DG6Q}}
+}"""
+
+# Dataset info
+urls_per_split = {
+    "train": "https://huggingface.co/datasets/mstz/post_operative/raw/main/post_operative.data"
+}
+features_types_per_config = {
+    "post_operative": {
+        "internal_temperature": datasets.Value("int8"),
+        "surface_temperature": datasets.Value("int8"),
+        "oxigen_saturation": datasets.Value("int8"),
+        "blood_pressure": datasets.Value("int8"),
+        "surface_temperature_stability": datasets.Value("int8"),
+        "internal_temperature_stability": datasets.Value("int8"),
+        "blood_pressure_stability": datasets.Value("int8"),
+        "perceived_comfort": datasets.Value("int8"),
+        "decision": datasets.ClassLabel(num_classes=3, names=("discharge", "hospital floor", "intensive care")),
+    },
+    "post_operative_binary": {
+		"internal_temperature": datasets.Value("int8"),
+        "surface_temperature": datasets.Value("int8"),
+        "oxigen_saturation": datasets.Value("int8"),
+        "blood_pressure": datasets.Value("int8"),
+        "surface_temperature_stability": datasets.Value("int8"),
+        "internal_temperature_stability": datasets.Value("int8"),
+        "blood_pressure_stability": datasets.Value("int8"),
+        "perceived_comfort": datasets.Value("int8"),
+        "decision": datasets.ClassLabel(num_classes=2, names=("discharge", "don't discharge")),
+    }
+}
+features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
+
+
+class PostOperativeConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(PostOperativeConfig, self).__init__(version=VERSION, **kwargs)
+        self.features = features_per_config[kwargs["name"]]
+
+
+class PostOperative(datasets.GeneratorBasedBuilder):
+    # dataset versions
+    DEFAULT_CONFIG = "post_operative"
+    BUILDER_CONFIGS = [
+        PostOperativeConfig(name="post_operative",
+                   description="PostOperative for regression."),
+        PostOperativeConfig(name="post_operative_binary",
+                   description="PostOperative for binary classification.")
+    ]
+
+
+    def _info(self):
+        info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
+                                    features=features_per_config[self.config.name])
+
+        return info
+    
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        downloads = dl_manager.download_and_extract(urls_per_split)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
+        ]
+    
+    def _generate_examples(self, filepath: str):
+        data = pandas.read_csv(filepath)
+        data = self.preprocess(data)
+
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row
+
+    def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
+        if self.config.name == "post_operative_binary":
+            data["decision"] = data["decision"].apply(lambda x: 1 if x > 1 else 0)
+
+        for feature in _ENCODING_DICS:
+            encoding_function = partial(self.encode, feature)
+            data.loc[:, feature] = data[feature].apply(encoding_function)
+        
+        data = data.reset_index()
+        data.drop("index", axis="columns", inplace=True)
+                
+        return data[list(features_types_per_config[self.config.name].keys())]
+
+    def encode(self, feature, value):
+        if feature in _ENCODING_DICS:
+            return _ENCODING_DICS[feature][value]
+        raise ValueError(f"Unknown feature: {feature}")