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Repository for Analysis of data hosted on UCI Machine Learning Archives - UCI-Data-Analysis/Boston Housing Dataset/Boston Housing/UCI Machine Learning Repository_ Housing Data Set.pdf at master · rupakc/UCI-Data-Analysis
task: Associated machine learning tasks e.g. classification, regression characteristics : Dataset types e.g. multivariate, sequential num_instances : Number of rows or samples
An Introduction to Statistical Learning: With Applications in R. Springer Publishing Company, Incorporated. A. Tsanas, A. Xifara: 'Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools', Energy and Buildings, Vol. 49, pp. 560-567, 2012
This is a python package to enable easy access to datasets in the UCI Machine Learning Repository. Note that this is not an official API. Any usage of datasets should be cited according to instructions in the UCI Machine Learning Repository. The project is at an early alpha stage, so suggestion for changes or additions are very welcome.
This is the case for only 5 datapoints, less than could be expected for 10,000 datapoints in our dataset. If at least one of the above failure modes is true, the process fails and the 'machine failure' label is set to 1. It is therefore not transparent to the machine learning method, which of the failure modes has caused the process to fail.
[Online; UCI Machine Learning Repository]. Andrzejak RG, Lehnertz K, Rieke C, Mormann F, David P, Elger CE (2001) Indications of nonlinear deterministic and finite dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state, Phys. Rev. E, 64, 061907
This project aims to develop machine learning models for the accurate calibration of sensor data, specifically addressing the issue of sensor drift in IoT devices. Sensor drift, caused by environmental conditions or ageing, can lead to decreased accuracy over time. Traditional recalibration methods ...
bank.csv with 10% of the examples and 17 inputs, randomly selected from 3 (older version of this dataset with less inputs). The smallest datasets are provided to test more computationally demanding machine learning algorithms (e.g., SVM). The classification goal is to predict if the client will subscribe (yes/no) a term deposit (variable y).
Apr 27, 2024 · Heart Disease Dataset (Most comprehensive) Content Heart disease is also known as Cardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated 17.9 million lives each year which is about 32 of all deaths globally.
Note that data in this repository dates back to 1987, the format across datasets are not consistent. Some inconsistencies include column separation and the way NA values are handled. Luckily, data in ucimlr follows a consistent structure that any R user can dive into.
