DARWIN
Donated on 5/11/2022
The DARWIN dataset includes handwriting data from 174 participants. The classification task consists in distinguishing Alzheimer’s disease patients from healthy people.
Dataset Characteristics
Tabular
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
-
# Instances
174
# Features
451
Dataset Information
For what purpose was the dataset created?
The DARWIN dataset was created to allow researchers to improve the existing machine learning methodologies for the prediction of Alzheimer's disease via handwriting analysis.
Has Missing Values?
No
Introductory Paper
By Nicole D. Cilia, Giuseppe De Gregorio , Claudio De Stefano, Francesco Fontanella, Angelo Marcelli, Antonio Parziale . 2022
Published in Journal
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| ID | Feature | Categorical | no | ||
| air_time1 | Feature | Integer | no | ||
| disp_index1 | Feature | Categorical | no | ||
| gmrt_in_air1 | Feature | Continuous | no | ||
| gmrt_on_paper1 | Feature | Continuous | no | ||
| max_x_extension1 | Feature | Integer | no | ||
| max_y_extension1 | Feature | Integer | no | ||
| mean_acc_in_air1 | Feature | Continuous | no | ||
| mean_acc_on_paper1 | Feature | Continuous | no | ||
| mean_gmrt1 | Feature | Continuous | no |
0 to 10 of 452
Dataset Files
| File | Size |
|---|---|
| data.csv | 723.1 KB |
| DARWIN.zip | 332.2 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset darwin = fetch_ucirepo(id=732) # data (as pandas dataframes) X = darwin.data.features y = darwin.data.targets # metadata print(darwin.metadata) # variable information print(darwin.variables)
Fontanella, F. (2022). DARWIN [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C55D0K.
Creators
Francesco Fontanella
fontanella@unicas.it
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.