牛津帕金森病检测数据集
该数据集包含31人的语音声学特征测量数据，用于帕金森病二元分类，共22个特征。
基本信息
资源简介
牛津帕金森病检测数据集
【数据集背景】
本数据集源站标题为《O-Memis/ParkinsonVoiceSVM》。源站首次发布：2024-10-25。
【数据内容】
源站原始描述：Study of classification of Parkinsons''s disease with dataset of voice features, by using Sci-kit learn library. # ParkinsonVoiceSVM "Parkinson''s Disease Detection using Machine Learning - Python" Project of classification of Parkinsons''s disease with dataset of voice features. Supervised classification is done by using Support Vector Machine model from Sci-kit learn library. ## Content 1) Files 2) Dataset and video tutorial 3) How to reference 4) Information about the project 5) Code Organizatio…
【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/O-Memis/ParkinsonVoiceSVM
使用许可：MIT。
【使用注意】
· 源站最后修改于 2024-10-26，引用时请注意版本时效。
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/O-Memis/ParkinsonVoiceSVM.git
curl -L -o repo.zip https://github.com/O-Memis/ParkinsonVoiceSVM/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录（使用方式）
ParkinsonVoiceSVM
“Parkinson’'s Disease Detection using Machine Learning - Python”
Project of classification of Parkinsons’'s disease with dataset of voice features. Supervised classification is done by using Support Vector Machine model from Sci-kit learn library.
Content
- Files
- Dataset and video tutorial
- How to reference
- Information about the project
- Code Organization
1-Files
Code file is “ParkinsonVoiceSVM.py” and dataset file is “parkinsons.csv” you should download these two.
There is also a model file called “svm_parkinson.joblib” to import the model in a system.
2-Dataset and video tutorial
Utilized by this video tutorial : Siddardhan
Codes in tutorial are changed & re-designed based on my own decisions and practices.
3-How to reference
Please refer with names or Github links which are Siddardhan S (tutorial owner), and Oğuzhan Memiş (this repository), and the source of the dataset.
Contacts are welcomed.
Dataset
Oxford Parkinson’‘s Disease Detection Dataset
2008-06-26
Cite: Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2008),’‘Suitability of dysphonia measurements for telemonitoring of Parkinson’‘s disease’',IEEE Transactions on Biomedical Engineering
4-Information about the project
Parkinson’'s is a neurological and progressive disease, which occurs from lack of some neurotransmitters in the brain such as Dopamine.
It harms the fine-tuned control of the movements of the body. As it progress, several symptoms such as tremor, body stiffness and loss of balance are observed.
Dataset:
Instances (samples): 195
Attributes (features): 22 + 1(label)
Focused on various acoustic properties of voice recordings, which are used to detect and analyze Parkinson’'s disease.
Voice measurements from 31 people, 23 with Parkinson’'s disease (PD).6 recordings per patient.
The main aim is discriminate healthy=0 and PD=1 as binary classification.
How these measurements are performed:
Voice Recording: Subjects are typically asked to sustain a vowel sound (often ‘‘ahhh’’) for several seconds.<br>
Signal Processing: The voice recordings are then processed using specialized software that can extract these acoustic features.<br>
MDVP: Many of these f
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？
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