机器学习 - Parkinsons Data Set（帕金森数据集）

Parkinsons Data Set(帕金森数据集)

数据摘要：

Oxford Parkinson's Disease Detection Dataset.This dataset is

composed of a range of biomedical voice measurements from 31 people, 23 with Parkinson's disease (PD). Each column in the table is a particular voice measure, and each row corresponds one of 195 voice recording from these individuals (\discriminate healthy people from those with PD, according to \column which is set to 0 for healthy and 1 for PD.

中文关键词：

帕金森,多变量,分类,UCI,

英文关键词：

Parkinsons,Multivariate,Classification,UCI,

数据格式：

TEXT

数据用途：

This data set is used for classification.

数据详细介绍：

Parkinsons Data Set

Abstract: Oxford Parkinson's Disease Detection Dataset Data Set Characteristics: Attribute Characteristics: Multivariate Number of 19Instances: 7 Number of Attributes23 : Missing Values? N/A Area: Life Real Date Donated 2008-06-26 Associated Tasks: Source:

Classification Number of Web 27541 Hits: The dataset was created by Max Little of the University of Oxford, in

collaboration with the National Centre for Voice and Speech, Denver, Colorado, who recorded the speech signals. The original study published the feature extraction methods for general voice disorders.

Data Set Information:

This dataset is composed of a range of biomedical voice measurements from 31 people, 23 with Parkinson's disease (PD). Each column in the table is a particular voice measure, and each row corresponds one of 195 voice

recording from these individuals (\to discriminate healthy people from those with PD, according to \column which is set to 0 for healthy and 1 for PD.

The data is in ASCII CSV format. The rows of the CSV file contain an instance corresponding to one voice recording. There are around six recordings per patient, the name of the patient is identified in the first column.For further information or to pass on comments, please contact Max Little (littlem '@' robots.ox.ac.uk).

Further details are contained in the following reference -- if you use this dataset, please 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 (to appear).

Attribute Information:

Matrix column entries (attributes):

name - ASCII subject name and recording number MDVP:Fo(Hz) - Average vocal fundamental frequency MDVP:Fhi(Hz) - Maximum vocal fundamental frequency MDVP:Flo(Hz) - Minimum vocal fundamental frequency

MDVP:Jitter(%),MDVP:Jitter(Abs),MDVP:RAP,MDVP:PPQ,Jitter:DDP - Several measures of variation in fundamental frequency

MDVP:Shimmer,MDVP:Shimmer(dB),Shimmer:APQ3,Shimmer:APQ5,MDVP:APQ,Shimmer:DDA - Several measures of variation in amplitude

NHR,HNR - Two measures of ratio of noise to tonal components in the voice status - Health status of the subject (one) - Parkinson's, (zero) - healthy RPDE,D2 - Two nonlinear dynamical complexity measures DFA - Signal fractal scaling exponent

spread1,spread2,PPE - Three nonlinear measures of fundamental frequency variation

数据预览：

点此下载完整数据集

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