The doctoral thesis, Enhancing Genetic Programming for Predictive Modeling, is about machine learning, more specifically predictive modeling, a field of computer science.

Transfer learning has attracted more attention in the machine-learning community recently. It aims to improve the learning performance on the domain of interest with the help of the knowledge acquired ...

Learn how to prevent overfitting or underfitting problems when using grid search and k-fold cross validation for machine learning models.

In machine learning, overfitting occurs when a statistical model accurately fits the data at hand but fails to describe the underlying pattern. ... Dubčáková, R. (2010). “Eureqa – software review,” in ...

Overfitting is also a factor in machine learning. It might emerge when a machine has been taught to scan for specific data one way, but when the same process is applied to a new set of data, the ...

Multiclass classification is one of the most fundamental tasks in data mining. However, traditional data mining methods rely on the model assumption, they generally can suffer from the overfitting ...

Landscape genetics—explicitly quantifying the effects of a heterogenous landscape on gene flow—is an important tool for both conservation biology and the control of invasive species and disease ...

To address this, the team developed PhyloFrame, a machine-learning tool that uses artificial intelligence to incorporate ...