datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bace_regression
Dataset Card for bace_regression
Dataset Summary
bace_regression is a dataset included in MoleculeNet. This dataset consists of Quantitative (IC50) binding results for a set of inhibitors of human β-secretase 1(BACE-1).
Dataset Structure
Data Fields
Each split contains
smiles: the SMILES representation of a molecule
selfies: the SELFIES representation of a molecule
target: the IC50 binding results
Data Splits
The dataset is split into… See the full description on the dataset page: https://huggingface.co/datasets/zpn/bace_regression.grant-scoring-release-gate-regression-fixtures
Grant-Scoring Release Gate Regression Fixtures
Test a grant-scoring configuration-change release gate without real applications. This CC BY 4.0 package contains 27 fully fictional regression fixtures: three local-policy scenarios for each of nine evaluation-fingerprint fields.
The changed fields are rubric version, policy context, resolved configuration, prompt bundle, tool schema, few-shot set, model identity, evidence cutoff and pipeline commit. Every row keeps the baseline… See the full description on the dataset page: https://huggingface.co/datasets/mheilimo/grant-scoring-release-gate-regression-fixtures.student-grades-regression
Student Grades Regression Dataset
This dataset contains student grades data for regression tasks. It is designed for demonstrating regression techniques and data quality methods.
Dataset Description
The dataset includes:
train.csv - Training data with student features and grade labels
test.csv - Test data for evaluation
This is a regression version of the student grades dataset, where the target variable is continuous.
Usage
import pandas as pd
# Load the… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/student-grades-regression.fairleap-driver-earnings-regression-500
Fairleap Driver Earnings Regression 500
📘 Dataset Overview
A small synthetic tabular dataset of ride-hailing driver work sessions, built for
the Fairleap AI project — a platform addressing income
uncertainty and wellbeing for Gojek/GOTO drivers in Indonesia. Each row is one work
session: when it happened, where, how long it ran, how many rides were completed, and
what it paid.
The dataset backs two regression targets: earnings (Indonesian Rupiah per session)
and… See the full description on the dataset page: https://huggingface.co/datasets/fairleap-ai/fairleap-driver-earnings-regression-500.URLs_FunctionalIntegration_Regression
URLs_FunctionalIntegration_Regression
tags: Machine Learning, Functional Integration, Regression
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'URLs_FunctionalIntegration_Regression' dataset comprises a collection of unique URLs from various music industry-related platforms, event pages, and tools that integrate functionalities of AI and ML for analyzing trends, predicting event attendance, and managing artist contracts. The… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/URLs_FunctionalIntegration_Regression.all_samples_Regressionfineweb-edu-gemini-annotations-portuguese-regressionKI_API_Regression_Dataset
KI_API_Regression_Dataset
tags: regression, API key analysis, machine learning, trend prediction
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'KI_API_Regression_Dataset' contains simulated data relevant to regression analysis for API key analysis in the context of AI applications. It includes various attributes that could be important for predicting trends or patterns in API usage related to AI technologies. This dataset… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/KI_API_Regression_Dataset.regression_dataset_tmdbwhisper_regression_AverageCSR_2columnsHouse_Prices_Advanced_Regression_Techniquesregression
Import pandas as pd
import pandas as pd
import json
data = [
("Today around 11:30am I realized that I've only ever worked in JavaScript and am wondering if I'm cooked...", 7),
("Today I learned how to check in. I'll be working on fixing my CoLab and starting to work on any datasets missed", 6),
("Today I finally figured out how to set up GitHub repositories and push my first project...", 8),
("Today I decided to dive into Python’s object-oriented programming...", 8)… See the full description on the dataset page: https://huggingface.co/datasets/MaryahGreene/regression.ai-5node-drift-buf-lag-tool-update-regression-v0.1
What this repo does
This dataset models regression cascades caused by model updates in tool-using AI systems. It detects when update-driven drift rises, safety buffers weaken due to partial canary coverage, governance lag delays rollback, and tool coupling propagates regressions across workflows, crossing the five-node cascade threshold into an unrecoverable update regression cascade.
This dataset models a five-node cascade: four interacting instability drivers and one emergent… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-5node-drift-buf-lag-tool-update-regression-v0.1.100entries_whisper_regression_AverageCSR_2columns_100entriesregression_datawhisper_4_selfprom_scores_regression_2columns