Improving Recall of software defect prediction models using association mining
Use of software product metrics in defect prediction studies highlights the utility of these metrics. Public availability of software defect data based on the product metrics has resulted in the development of defect prediction models. These models ...
Fast low rank representation based spatial pyramid matching for image classification
Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM incorporates Sparse Code (SC) instead of Vector Quantization (VQ) into ...
Improving network topology-based protein interactome mapping via collaborative filtering
High-throughput screening (HTS) techniques enable massive identification of protein-protein interactions (PPIs). Nonetheless, it is still intractable to observe the full mapping of PPIs. With acquired PPI data, scalable and inexpensive computation-based ...
An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage
DL Query is used to extract information from content stored in the ontology.The Felder Silverman model is used to determine learning styles of learner's.JADE agents monitor learner's behavior to provide adaptive learning.Deployments on cloud enable ...
Online learning the consensus of multiple correspondences between sets
When several subjects solve the assignment problem of two sets, differences on the correspondences computed by these subjects may occur. These differences appear due to several factors. For example, one of the subjects may give more importance to some ...
Semi-supervised cluster-and-label with feature based re-clustering to reduce noise in Thai document images
We proposed a novel noise reduction method for document images.Semi-supervised learning is applied to classify noise from character components.The proposed method is suitable for Non-Latin based scripts i.e. Thai document image.We proposed an enhance ...
A knowledge-based evolutionary proactive scheduling approach in the presence of machine breakdown and deterioration effect
This paper considers proactive scheduling in response to stochastic machine breakdown under deteriorating production environments, where the actual processing time of a job gets longer along with machine's usage and age. It is assumed that a job's ...
Trust Description and Propagation System
Trust plays a vital role in many successful applications in computer science. However, existing work fails to provide a systematic analysis of trust in a consistent logic framework, resulting in the fact that trust can only be used pragmatically and ...
An approach to determining the integrated weights of decision makers based on interval number group decision matrices
In this paper, we develop an approach to determining the integrated weights of decision makers (DMs) with interval numbers in multiple attribute group decision making (MAGDM) problems. We first map the interval numbers of each DM's decision matrix into ...
Location difference of multiple distances based k-nearest neighbors algorithm
The "location difference of multiple distances" and a method LDMDBA are proposed.LDMDBA has a time complexity of O(logdnlogn) and does not rely on tree structures.Only LDMDBA can be efficiently applied to high dimensional data.LDMDBA has a time ...
Decision-making model to generate novel emergency response plans for improving coordination during large-scale emergencies
Developing joint emergency response plans is an effective method to coordinate multi-agency response endeavors. This study presents a novel emergency response plan structure that considers emergency command operation requirements, such as explicitly ...
Robust support vector data description for outlier detection with noise or uncertain data
We propose two new SVDD models which improve the robustness to noise.Cutoff distance-based local density can mitigate the effect of noise towards SVDD.Tolerated gap of SVDD with ε-insensitive loss can improve generalization performance. As an example of ...
Sensor-based human activity recognition system with a multilayered model using time series shapelets
We exploit time series shapelets for complex human activity recognition.We present a multilayered activity model to represent four types of activities.We implement a prototype system based on smartphone for human activity recognition.Daily living and ...
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems
- Luís P.F. Garcia,
- José A. Sáez,
- Julián Luengo,
- Ana C. Lorena,
- André C.P.L.F. de Carvalho,
- Francisco Herrera
Noise filters are preprocessing techniques designed to improve data quality in classification tasks by detecting and eliminating examples that contain errors or noise. However, filtering can also remove correct examples and examples containing valuable ...
An analysis of fully fuzzy linear programming with fuzzy decision variables through logistics network design problem
Recently, there is a growing attention by the researchers to solve and interpret the analysis of fully fuzzy linear programming problems in which all of the parameters as well as the decision variables are considered as fuzzy numbers. Under a fully ...
Intelligent algorithms for a new joint replenishment and synthetical delivery problem in a warehouse centralized supply chain
We provide a new designed delivery process of JRD with vary number of customers.We propose procedures to deal with three cases in the new delivery process.Three algorithms, QEA, DE and QDE are redesigned to solve the new JRD model.Superiorities of DE ...
Quadruple Transfer Learning
Transfer learning focuses on leveraging the knowledge in source domains to complete the learning tasks in target domains, where the data distributions of the source and target domains are related but different in accordance with original features. To ...
A generalized Gilbert algorithm and an improved MIES for one-class support vector machine
The primal maximum margin problem of OCSVM is equivalent to a nearest point problem.A generalized Gilbert (GG) algorithm is proposed to solve the nearest point problem.An improved MIES is developed for the Gaussian kernel parameter selection.The GG ...
Gravitational fixed radius nearest neighbor for imbalanced problem
We use the gravitational scenario into the fixed radius nearest neighbor rule.The proposed GFRNN deals with imbalanced classification problem.GFRNN does not need any manual parameter setting or coordination.Comparison experiments on 40 datasets validate ...
An uncertainty-based approach
Since itemset mining was proposed, various approaches have been devised, ranging from processing simple item-based databases to dealing with more complex databases including sequence, utility, or graph information. Especially, in contrast to the mining ...