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Mitigating the multicollinearity problem and its machine learning approach: a review
Technologies have driven big data collection across many fields, such as genomics and
business intelligence. This results in a significant increase in variables and data points …
business intelligence. This results in a significant increase in variables and data points …
The missing pieces of artificial intelligence in medicine
Stakeholders across the entire healthcare chain are looking to incorporate artificial
intelligence (AI) into their decision-making process. From early-stage drug discovery to …
intelligence (AI) into their decision-making process. From early-stage drug discovery to …
A county-level soybean yield prediction framework coupled with XGBoost and multidimensional feature engineering
Yield prediction is essential in food security, food trade, and field management. However,
due to the associated complex formation mechanisms of yield, accurate and timely yield …
due to the associated complex formation mechanisms of yield, accurate and timely yield …
Neuzz: Efficient fuzzing with neural program smoothing
Fuzzing has become the de facto standard technique for finding software vulnerabilities.
However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger …
However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger …
A comparison of regression techniques for estimation of above-ground winter wheat biomass using near-surface spectroscopy
Above-ground biomass (AGB) provides a vital link between solar energy consumption and
yield, so its correct estimation is crucial to accurately monitor crop growth and predict yield …
yield, so its correct estimation is crucial to accurately monitor crop growth and predict yield …
[HTML][HTML] Estimation of above-ground biomass of winter wheat based on consumer-grade multi-spectral UAV
One of the problems of optical remote sensing of crop above-ground biomass (AGB) is that
vegetation indices (VIs) often saturate from the middle to late growth stages. This study …
vegetation indices (VIs) often saturate from the middle to late growth stages. This study …
Malware detection: a framework for reverse engineered android applications through machine learning algorithms
Today, Android is one of the most used operating systems in smartphone technology. This is
the main reason, Android has become the favorite target for hackers and attackers …
the main reason, Android has become the favorite target for hackers and attackers …
A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones
Background Undernutrition is the main cause of child death in develo** countries. This
paper aimed to explore the efficacy of machine learning (ML) approaches in predicting …
paper aimed to explore the efficacy of machine learning (ML) approaches in predicting …
[HTML][HTML] Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain
Various diffusion MRI (dMRI) measures have been proposed for characterising tissue
microstructure over the last 15 years. Despite the growing number of experiments using …
microstructure over the last 15 years. Despite the growing number of experiments using …
Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA
Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across
spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk …
spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk …