Ehsan Bitaraf, Maryam Jafarpour Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation Parsing https://arxiv.org/abs/2410.04602
Five Years of COVID-19 Discourse on Instagram: A Labeled Instagram Dataset of Over Half a Million Posts for Multilingual Sentiment Analysis https://arxiv.org/abs/2410.03293
on that note, R is a middling programming language with (some) excellent libraries, and the new ryp library has made it very easy to run R inside python using arrow as a data transport layer. Example of passing a dataset into R, fitting a GAM using mgcv, then moving preds into py
Do you use every vote, or do you use votes of consequence like Matt Elliott's tracker? I tried coding his as progressive/conservative last term to see the coalitions. Tough to see differences with the full dataset because of unanimous/voice votes.
Fred Moten is coming to speak at my institution and I am going to miss the talk because I have to attend a meeting about an analysis of a dataset and somehow this is what my life has become. plus fleeing hurricanes
DSI and International nonprofit GRAIN collaborated to develop a new dataset on carbon credit land projects This dataset will help GRAIN highlight the social and environmental impacts of 279 large-scale carbon-credit projects corporations have initiated across the world since 2016
DSI and International nonprofit GRAIN collaborated to develop a new dataset on carbon credit land projects This dataset will help GRAIN highlight the social and environmental impacts of 279 large-scale carbon-credit projects corporations have initiated across the world since 2016
Haechan Kim, Junho Myung, Seoyoung Kim, Sungpah Lee, Dongyeop Kang, Juho Kim LearnerVoice: A Dataset of Non-Native English Learners' Spontaneous Speech https://arxiv.org/abs/2407.04280
The dataset I use to power that feed isn't perfect and I may have missed some follow activity when you followed people back. You can try unfollowing/following them again to see if that fixes it.
What is Anomaly Detection? Anomaly detection refers to the process of identifying data points, observations, or patterns that deviate significantly from the normal behavior of a dataset. aicompetence.org/svms-in-anom...
Support Vector Machines (SVMs) excel at anomaly detection, identifying outliers in high-dimensional data with precision in complex datasets.