A hybrid approach using oversampling technique and cost‐sensitive learning for bankruptcy prediction
The diagnosis of bankruptcy companies becomes extremely important for business owners,
banks, governments, securities investors, and economic stakeholders to optimize the …
banks, governments, securities investors, and economic stakeholders to optimize the …
[PDF][PDF] Brent Oil Price Prediction Using Bi-LSTM Network.
Brent oil price fluctuates continuously causing instability in the economy. Therefore, it is
essential to accurately predict the trend of oil prices, as it helps to improve profits for …
essential to accurately predict the trend of oil prices, as it helps to improve profits for …
The lattice‐based approaches for mining association rules: a review
The traditional methods for mining association rules (ARs) include two phrases: mining
frequent itemsets (FIs)/frequent closed itemsets (FCIs)/frequent maximal itemsets (FMIs) and …
frequent itemsets (FIs)/frequent closed itemsets (FCIs)/frequent maximal itemsets (FMIs) and …
Efficient approach for incremental weighted erasable pattern mining with list structure
Erasable pattern mining is one of the important fields of frequent pattern mining. It diagnoses
and solves the economic problems that arise in the manufacturing industry. The real-world …
and solves the economic problems that arise in the manufacturing industry. The real-world …
An efficient algorithm for mining top-rank-k frequent patterns
Mining top-rank-k frequent patterns is a popular data mining task, which consists of
discovering the patterns in a transaction database that belong to the k first ranks in terms of …
discovering the patterns in a transaction database that belong to the k first ranks in terms of …
Mining erasable itemsets with subset and superset itemset constraints
Erasable itemset (EI) mining, a branch of pattern mining, helps managers to establish new
plans for the development of new products. Although the problem of mining EIs was first …
plans for the development of new products. Although the problem of mining EIs was first …
Efficient algorithms for mining top-rank-k erasable patterns using pruning strategies and the subsume concept
Mining erasable patterns (EPs) is one of the emerging tasks in data mining which helps
factory managers to establish plans for the development of new systems of products …
factory managers to establish plans for the development of new systems of products …
SPPC: a new tree structure for mining erasable patterns in data streams
Abstract Discovering Erasable Patterns (EPs) consists of identifying product parts that will
produce a small profit loss if their production is stopped. It is a data mining problem that has …
produce a small profit loss if their production is stopped. It is a data mining problem that has …
Efficient algorithms for mining erasable closed patterns from product datasets
Finding knowledge from large data sets to use in intelligent systems becomes more and
more important in the Internet era. Pattern mining, classification, text mining, and opinion …
more important in the Internet era. Pattern mining, classification, text mining, and opinion …
IME: Efficient list-based method for incremental mining of maximal erasable patterns
R Davashi - Pattern Recognition, 2024 - Elsevier
Erasable pattern mining can help factories facing a financial crisis increase productivity by
identifying and eliminating unprofitable products. The Flag-GenMax-EI algorithm extracts …
identifying and eliminating unprofitable products. The Flag-GenMax-EI algorithm extracts …