Improved reptile search optimization algorithm using chaotic map and simulated annealing for feature selection in medical field
The increased volume of medical datasets has produced high dimensional features,
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …
Tri-staged feature selection in multi-class heterogeneous datasets using memetic algorithm and cuckoo search optimization
Classification algorithms and their preprocessing operations usually performs on feature
selection on homogeneous or heterogeneous attributes, binary or multi-class labels …
selection on homogeneous or heterogeneous attributes, binary or multi-class labels …
Relative entropy of correct proximal policy optimization algorithms with modified penalty factor in complex environment
In the field of reinforcement learning, we propose a Correct Proximal Policy Optimization
(CPPO) algorithm based on the modified penalty factor β and relative entropy in order to …
(CPPO) algorithm based on the modified penalty factor β and relative entropy in order to …
[PDF][PDF] Genetic Algorithm Combined with the K-Means Algorithm: A Hybrid Technique for Unsupervised Feature Selection.
The dimensionality of data is increasing very rapidly, which creates challenges for most of
the current mining and learning algorithms, such as large memory requirements and high …
the current mining and learning algorithms, such as large memory requirements and high …