UCI Machine Learning Repository Datasets
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UCI Machine Learning Repository Datasets

One of the earliest known datasets used for evaluating classification methods. 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests. Predict whether annual income of an individual exceeds $50K/yr based on census data. Diagnostic Wisconsin Breast Cancer Database. The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit. Predict student performance in secondary education (high school). This is a transactional data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. Derived from simple hierarchical decision model, this database may be useful for testing constructive induction and structure discovery methods.

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相关论文

4

A data-driven dimensionality-reduction algorithm for the exploration of patterns in biomedical data

Md Tauhidul IslamLei Xing
Nature Biomedical Engineering
2020
2020/11/2
00 p.1-12
Dimensionality reduction is widely used in the visualization, compression, exploration and classification of data. Yet a generally applicable solution remains unavailable. Here, we report an accurate and broadly applicable data-driven algorithm for dimensionality reduction. The algorithm, which we n...
Applied mathematicsComputational scienceSoftwareStatistics
10.1038/S41551-020-00635-3
ISSN:2157-846X

Kernel approximation using analogue in-memory computing

Julian BüchelGiacomo CamposampieroAthanasios VasilopoulosCorey LammieManuel Le Gallo7
Nature Machine Intelligence
2024
2024/12/13
Vol.6 No.12 p.1605-1615
Kernel functions are vital ingredients of several machine learning (ML) algorithms but often incur substantial memory and computational costs. We introduce an approach to kernel approximation in ML algorithms suitable for mixed-signal analogue in-memory computing (AIMC) architectures. Analogue in-me...
Computer scienceElectrical and electronic engineering
10.1038/S42256-024-00943-2
ISSN:2522-5839

Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality

Stamatakis EmmanuelAhmadi Matthew N.Gill Jason M. R.Thøgersen-Ntoumani CecilieGibala Martin J.7
Nature Medicine
2022
2022/12/8
Vol.28 No.12 p.2521-2529
Wearable devices can capture unexplored movement patterns such as brief bursts of vigorous intermittent lifestyle physical activity (VILPA) that is embedded into everyday life, rather than being done as leisure time exercise. Here, we examined the association of VILPA with all-cause, cardiovascular ...
Cardiovascular diseasesEpidemiologyRisk factors
10.1038/S41591-022-02100-X
ISSN:1078-8956

Gaining biological insights through supervised data visualization

Jake S. RhodesAdrien AumonSacha MorinMarc GirardCatherine Larochelle19
Nature Computational Science
2026
2026/6/30
00 p.1-21
Dimensionality-reduction-based visualization is essential for interpreting complex biological data. Yet, unsupervised methods such as t-distributed stochastic neighbor embedding, Uniform Manifold Approximation and Projection, and Isomap reflect only the dominant data structure, which may not align w...
Machine learningMultiple sclerosis
10.1038/S43588-026-00999-7
ISSN:2662-8457