updated to datasets 4.*

README.md

@@ -1,21 +1,35 @@
 ---
-language:
-- en
+configs:
+- config_name: seeds_0
+  data_files:
+  - path: seeds_0/train.csv
+    split: train
+  default: true
+- config_name: seeds_1
+  data_files:
+  - path: seeds_1/train.csv
+    split: train
+  default: false
+- config_name: seeds_2
+  data_files:
+  - path: seeds_2/train.csv
+    split: train
+  default: false
+- config_name: seeds
+  data_files:
+  - path: seeds/train.csv
+    split: train
+  default: false
+language: en
+license: cc
+pretty_name: Seeds
+size_categories: 1M<n<10M
 tags:
-- seeds
 - tabular_classification
 - binary_classification
 - multiclass_classification
-- UCI
-pretty_name: Page Blocks
-size_categories:
-- 1K<n<10K
 task_categories:
 - tabular-classification
-configs:
-- seeds
-- seeds_binary
-license: cc
 ---
 # Post Operative
 The [Seeds dataset](https://archive-beta.ics.uci.edu/dataset/236/seeds) from the [UCI repository](https://archive-beta.ics.uci.edu/).

seeds.py

@@ -1,136 +0,0 @@
-"""Seeds Dataset"""
-
-from typing import List
-from functools import partial
-
-import datasets
-
-import pandas
-
-
-VERSION = datasets.Version("1.0.0")
-
-_ENCODING_DICS = {}
-
-DESCRIPTION = "Seeds 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_seeds_236,
-  author       = {Charytanowicz,Magorzata, Niewczas,Jerzy, Kulczycki,Piotr, Kowalski,Piotr & Lukasik,Szymon},
-  title        = {{seeds}},
-  year         = {2012},
-  howpublished = {UCI Machine Learning Repository},
-  note         = {{DOI}: \\url{10.24432/C5H30K}}
-}
-"""
-
-# Dataset info
-urls_per_split = {
-    "train": "https://huggingface.co/datasets/mstz/seeds/raw/main/seeds.csv"
-}
-features_types_per_config = {
-    "seeds": {
-        "area": datasets.Value("float64"),
-        "perimeter": datasets.Value("float64"),
-        "compactness": datasets.Value("float64"),
-        "length": datasets.Value("float64"),
-        "width": datasets.Value("float64"),
-        "asymmetry": datasets.Value("float64"),
-        "length_grove": datasets.Value("float64"),
-        "class": datasets.ClassLabel(num_classes=3),
-    },
-    "seeds_0": {
-		"area": datasets.Value("float64"),
-        "perimeter": datasets.Value("float64"),
-        "compactness": datasets.Value("float64"),
-        "length": datasets.Value("float64"),
-        "width": datasets.Value("float64"),
-        "asymmetry": datasets.Value("float64"),
-        "length_grove": datasets.Value("float64"),
-        "class": datasets.ClassLabel(num_classes=2),
-    },
-    "seeds_1": {
-		"area": datasets.Value("float64"),
-        "perimeter": datasets.Value("float64"),
-        "compactness": datasets.Value("float64"),
-        "length": datasets.Value("float64"),
-        "width": datasets.Value("float64"),
-        "asymmetry": datasets.Value("float64"),
-        "length_grove": datasets.Value("float64"),
-        "class": datasets.ClassLabel(num_classes=2),
-    },
-    "seeds_2": {
-		"area": datasets.Value("float64"),
-        "perimeter": datasets.Value("float64"),
-        "compactness": datasets.Value("float64"),
-        "length": datasets.Value("float64"),
-        "width": datasets.Value("float64"),
-        "asymmetry": datasets.Value("float64"),
-        "length_grove": datasets.Value("float64"),
-        "class": datasets.ClassLabel(num_classes=2),
-    },
-}
-features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
-
-
-class SeedsConfig(datasets.BuilderConfig):
-    def __init__(self, **kwargs):
-        super(SeedsConfig, self).__init__(version=VERSION, **kwargs)
-        self.features = features_per_config[kwargs["name"]]
-
-
-class Seeds(datasets.GeneratorBasedBuilder):
-    # dataset versions
-    DEFAULT_CONFIG = "seeds"
-    BUILDER_CONFIGS = [
-        SeedsConfig(name="seeds", description="Seeds for multiclass classification."),
-        SeedsConfig(name="seeds_0", description="Seeds for binary classification."),
-        SeedsConfig(name="seeds_1", description="Seeds for binary classification."),
-        SeedsConfig(name="seeds_2", description="Seeds 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:
-        data["class"] = data["class"].apply(lambda x: x - 1)
-
-        if self.config.name == "seeds_0":
-            data["class"] = data["class"].apply(lambda x: 1 if x == 0 else 0)
-        elif self.config.name == "seeds_1":
-            data["class"] = data["class"].apply(lambda x: 1 if x == 1 else 0)
-        elif self.config.name == "seeds_2":
-            data["class"] = data["class"].apply(lambda x: 1 if x == 2 else 0)
-
-        for feature in _ENCODING_DICS:
-            encoding_function = partial(self.encode, feature)
-            data.loc[:, feature] = data[feature].apply(encoding_function)
-                
-        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}")

seeds/train.csv

@@ -0,0 +1,211 @@
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+12.3,13.34,0.8684,5.243,2.974,5.637,5.063,2

seeds.csv → seeds_0/train.csv

@@ -6,7 +6,7 @@ area,perimeter,compactness,length,width,asymmetry,length_grove,class
 16.14,14.99,0.9034,5.658,3.562,1.355,5.175,1
 14.38,14.21,0.8951,5.386,3.312,2.462,4.956,1
 14.69,14.49,0.8799,5.563,3.259,3.586,5.219,1
-14.11,14.1,0.8911,5.42,3.302,2.7,5,1
+14.11,14.1,0.8911,5.42,3.302,2.7,5.0,1
 16.63,15.46,0.8747,6.053,3.465,2.04,5.877,1
 16.44,15.25,0.888,5.884,3.505,1.969,5.533,1
 15.26,14.85,0.8696,5.714,3.242,4.543,5.314,1
@@ -34,7 +34,7 @@ area,perimeter,compactness,length,width,asymmetry,length_grove,class
 14.09,14.41,0.8529,5.717,3.186,3.92,5.299,1
 13.94,14.17,0.8728,5.585,3.15,2.124,5.012,1
 15.05,14.68,0.8779,5.712,3.328,2.129,5.36,1
-16.12,15,0.9,5.709,3.485,2.27,5.443,1
+16.12,15.0,0.9,5.709,3.485,2.27,5.443,1
 16.2,15.27,0.8734,5.826,3.464,2.823,5.527,1
 17.08,15.38,0.9079,5.832,3.683,2.956,5.484,1
 14.8,14.52,0.8823,5.656,3.288,3.112,5.309,1
@@ -69,143 +69,143 @@ area,perimeter,compactness,length,width,asymmetry,length_grove,class
 14.01,14.29,0.8625,5.609,3.158,2.217,5.132,1
 14.37,14.39,0.8726,5.569,3.153,1.464,5.3,1
 12.73,13.75,0.8458,5.412,2.882,3.533,5.067,1
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