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Found 5 papers, 3 papers with code
FeatGeNN: Improving Model Performance for Tabular Data with Correlation-based Feature Extraction
Automated Feature Engineering (AutoFE) has become an important task for any machine learning project, as it can help improve model performance and gain more information for statistical analysis.
A Decidability-Based Loss Function
Nowadays, deep learning is the standard approach for a wide range of problems, including biometrics, such as face recognition and speech recognition, etc.
Applying Genetic Programming to Improve Interpretability in Machine Learning Models
Explainable Artificial Intelligence (or xAI) has become an important research topic in the fields of Machine Learning and Deep Learning.
BIG-bench Machine Learning
Explainable artificial intelligence
+1
Forecasting in Non-stationary Environments with Fuzzy Time Series
In this approach, we employ Non-Stationary Fuzzy Sets, in which perturbation functions are used to adapt the membership function parameters in the knowledge base in response to statistical changes in the time series.
Towards an Effective and Efficient Deep Learning Model for COVID-19 Patterns Detection in X-ray Images
Thus, the main goal of this work is to propose an accurate yet efficient method in terms of memory and processing time for the problem of COVID-19 screening in chest X-rays.
