癌症数据集
用于癌症良恶性分类的表格数据集，包含细胞核特征，经预处理后使用SVM分类器性能优异。
基本信息
资源简介
癌症数据集
【数据内容】
源站原始描述：This was a problem statement where we had to determine wheter the type of cancer was benign or malignant. Dataset had few empty values in the column named ''Bare Nuclei'', dropped the corresp
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://github.com/aayushs879/Cancer-Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
git clone https://github.com/aayushs879/Cancer-Dataset.git
curl -L -o repo.zip https://github.com/aayushs879/Cancer-Dataset/archive/refs/heads/master.zip
unzip repo.zip
源站 README 摘录（使用方式）
Cancer-Dataset
This was a problem statement where we had to determine wheter the type of cancer was benign or malignant. Dataset had few empty values in the column named ‘‘Bare Nuclei’’, dropped the corresponding rows so as to remove any kind of noise. Two features had a very high value of correlation so dropped one of them. Features were mostly on a similar scale. Finally implemented a Support Vector Classifier with a gaussian kernel and the mean recall score found on a k fold cross validation tehnique was 0.99 and the mean f score was 0.93.
数据加载示例（表格/文本类）
import pandas as pd, glob, os
files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
