Machine Learning

Dataset asscociated with a paper in IEEE Transactions on Pattern Analysis and Machine Intelligence

"The perils and pitfalls of block design for EEG classification experiments"

DOI: 10.1109/TPAMI.2020.2973153

If you use this code or data, please cite the above paper.


This file contains Python code to extract the single-diode model parameters from the Photovoltaic IV-curve. 


The dataset consists of reviews for various hotels throughout the world and data columns range from Location, Trip Type to various parameters of reviewing with individual review score. The data can be preprocessed and used for various purposes ranging from review categorization, topic extraction, sentiment analysis, location based quality calculation etc. Trustworthy real world data comes handy now-a-days and is tough to get a grasp on. So this dataset will be a good contribution for the researcher community as well as professionals. 



iSignDB: A biometric signature database created using smartphone

Suraiya Jabin, Sumaiya Ahmad, Sarthak Mishra, and Farhana Javed Zareen

Department of Computer Science, Jamia Millia Islamia, New Delhi-110025, India

It's a database of biometric signatures recorded using sensors present in a smartphone. ​The dataset iSignDB is created to implement a novel anti-spoof biometric signature authentication for smartphone users.


Wine has been popular with the public for centuries; in the market, there are a variety of wines to choose from. Among all, Bordeaux, France, is considered as the most famous wine region in the world. In this paper, we try to understand Bordeaux wines made in the 21st century through Wineinformatics study. We developed and studied two datasets: the first dataset is all the Bordeaux wine from 2000 to 2016; and the second one is all wines listed in a famous collection of Bordeaux wines, 1855 Bordeaux Wine Official Classification, from 2000 to 2016.



Intending to cover the existing gap regarding behavioral datasets modelling interactions of users with individual a multiple devices in Smart Office to later authenticate them continuously, we publish the following collection of datasets, which has been generated after having five users interacting for 60 days with their personal computer and mobile devices. Below you can find a brief description of each dataset.



Stable and efficient walking strategies for humanoid robots usually relies on assumptions regarding terrain characteristics. If the robot is able to classify the ground type at the footstep moment, it is possible to take preventive actions to avoid falls and to reduce energy consumption. 

This dataset contains raw data from 10 inertial and torque sensors of a humanoid robot, sampled after the impact between foot and ground. There are two types of data: simulated using gazebo and data from a real robot.


While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally leveraged as well to distort political elections and manipulate constituents. In the paper at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish general election.


Extracting the boundaries of Photovoltaic (PV) plants is essential in the process of aerial inspection and autonomous monitoring by aerial robots. This method provides a clear delineation of the utility-scale PV plants’ boundaries for PV developers, Operation and Maintenance (O&M) service providers for use in aerial photogrammetry, flight mapping, and path planning during the autonomous monitoring of PV plants.