IEEE

Classification Feature Optimization for Global Wetlands Mapping

Abstract: Wetlands play an important role in supporting biodiversity conservation and helping sustainable development. Time series wetland classification requires a series of sample sets acquired at ...
Frontiers

Anomaly detection in netflow traffic: workflow for dataset preparation and analysis

Information and communication technology (ICT) is crucial for maintaining efficient communications, enhancing processes, and enabling digital transformation. As ICT becomes increasingly significant in ...
IEEE

SHAP-Based Feature Selection for Enhanced Unsupervised Labeling

Abstract: Manual dataset labeling is expensive, time-consuming, and susceptible to noise and inaccuracies, often necessitating significant financial investments with risks of inconsistencies from ...
GitHub

[Feature]: Consolidate performance benchmark datasets

On vLLM we have two main benchmark scripts (benchmark_throughput.py and benchmark_serving.py) to measure the performance of vLLM. However, the dataset sampling functions are defined within each script ...
Wired

Harvard Is Releasing a Massive Free AI Training Dataset Funded by OpenAI and Microsoft

Harvard University announced Thursday it’s releasing a high-quality dataset of nearly 1 million public-domain books that could be used by anyone to train large language models and other AI tools. The ...
GitHub

[Feature Request] Update Datasets Version, so that lmms-eval can be used in Offline Environment

I encountered a similar issue as This one, when running lmms-eval with an offline machine(no Internet). load_dataset method still tries to reach Hugging Face Hub when I set HF_DATASETS_OFFLINE to 1. I ...
Computer Weekly

AI in the enterprise: How to build an AI dataset

Finding and acquiring the right data to build an enterprise dataset is perhaps the most critical task facing organisations that want to build their own artificial intelligence (AI) models. Even with ...
marktechpost

AnyGraph: An Effective and Efficient Graph Foundation Model Designed to Address the Multifaceted Challenges of Structure and Feature Heterogeneity Across Diverse Graph Datasets

Graph learning focuses on developing advanced models capable of analyzing and processing relational data structured as graphs. This field is essential in various domains, including social networks, ...
Scientific Research Publishing

Chouhan, S., Singh, D. and Singh, A. (2016) An Improved Feature Selection and Classification Using Decision Tree for Crop Datasets.

ABSTRACT: In agriculture sector, machine learning has been widely used by researchers for crop yield prediction. However, it is quite difficult to identify the most critical features from a dataset.
Scientific Research Publishing

Chen, C., Tsai, Y., Chang, F. and Lin, W. (2020) Ensemble Feature Selection in Medical Datasets: Combining Filter, Wrapper, and Embedded Feature Selection Results. Expert ...

ABSTRACT: In agriculture sector, machine learning has been widely used by researchers for crop yield prediction. However, it is quite difficult to identify the most critical features from a dataset.