异质数据中用于聚类和预测的贝叶斯集成树(BET)数据集

数据集获取（Figshare）

• 源站标题：Bayesian Ensemble Trees (BET) for Clustering and Prediction in Heterogeneous Data
• DOI：10.6084/m9.figshare.1568196.v1
• 发布日期：2015-09-24
• 文件数：2 个
• 文件总体积：453.72 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Bayesian_Ensemble_Trees_BET_for_Clustering_and_Prediction_in_Heterogeneous_Data/1568196

命令行下载

curl -L -o "BETcode.zip" "https://ndownloader.figshare.com/files/2349870"
curl -L -o "suppS1.pdf" "https://ndownloader.figshare.com/files/2349871"

文件清单

• BETcode.zip（18.23 KB）
• suppS1.pdf（435.49 KB）

文件总体积 453.72 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

We propose a novel “tree-averaging” model that uses the ensemble of classification and regression trees (CART). Each constituent tree is estimated with a subset of similar data. We treat this grouping of subsets as Bayesian ensemble trees (BET) and model them as a Dirichlet process. We show that BET determines the optimal number of trees by adapting to the data heterogeneity. Compared with the other ensemble methods, BET requires much fewer trees and shows equivalent prediction accuracy using weighted averaging. Moreover, each tree in BET provides variable selection criterion and interpretation for each subset. We developed an efficient estimating procedure with improved estimation strategies in both CART and mixture models. We demonstrate these advantages of BET with simulations and illustrate the approach with a real-world data example involving regression of lung function measurements obtained from patients with cystic fibrosis. Supplementary materials for this article are available online.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.1568196.v1（source: https://tandf.figshare.com/articles/dataset/Bayesian_Ensemble_Trees_BET_for_Clustering_and_Prediction_in_Heterogeneous_Data/1568196）。