A binary PSO-based ensemble under-sampling model for rebalancing imbalanced training data
Ensemble technique and under-sampling technique are both effective tools used for
imbalanced dataset classification problems. In this paper, a novel ensemble method …
imbalanced dataset classification problems. In this paper, a novel ensemble method …
Multi-Objective Particle Swarm Optimization Based Preprocessing of Multi-Class Extremely Imbalanced Datasets
Today's datasets are usually very large with many features and making analysis on such
datasets is really a tedious task. Especially when performing classification, selecting …
datasets is really a tedious task. Especially when performing classification, selecting …
Multi‐armed bandit heterogeneous ensemble learning for imbalanced data
One of the most widely used approaches to the class‐imbalanced issue is ensemble
learning. The base classifier is trained using an unbalanced training set in the conventional …
learning. The base classifier is trained using an unbalanced training set in the conventional …
Handling imbalanced data classification problem using artificial immune system with mahalanobis distance
D Jitkongchuen, W Sukpongthai - 2019 20th IEEE/ACIS …, 2019 - ieeexplore.ieee.org
Most of the data in the classification domain are imbalanced data, meaning that the answers
of each class are not the same. The data prediction in the majority class has been accurate …
of each class are not the same. The data prediction in the majority class has been accurate …
Binary Interactive Search Based Facelift Feature Selection Method for Household Classification Data on Smart Electricity Meter Data
M Suresh, MS Anbarasi - 2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
Smart meter data is one among a set of massive data where there are infinite number of
features are still inside it which in need of an effective mining approach for extracting from it …
features are still inside it which in need of an effective mining approach for extracting from it …
Evaluation of database balancing techniques for road accident severity classification employing Artificial Neural Network
Uma característica inerente aos bancos de dados de acidentes rodoviários refere-se ao
desequilíbrio existente entre o número de observações associadas às ocorrências dos …
desequilíbrio existente entre o número de observações associadas às ocorrências dos …
Data mining techniques for road accidentes: Clustering versus complex netwoks
This work analyses the performance of grouping methods based on complex networks and
clusters, in order to identify main road accident groups and risk factors. The research …
clusters, in order to identify main road accident groups and risk factors. The research …
Characterization of changes in dynamic multi-objective optimization problems
S Sahmoud - 2019 - search.proquest.com
Dinamik çok-amaçlı eniyileme problemleri (DÇAEP) on yıldan daha uzun bir süredir farklı
alanlarda çalışan araştırmacıların ilgisini çekmiştir. Zamana bağlı olarak, bir veya birden …
alanlarda çalışan araştırmacıların ilgisini çekmiştir. Zamana bağlı olarak, bir veya birden …