Sets and Classes as Many

MMDT: Multi-Objective Memetic Rule Learning from Decision Tree

In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...

Semi-θ-Open Sets and New Classes of Maps

On Pre-θ-Open Sets and Two Classes of Functions

Skew-slash distribution and its application in topics regression

In many issues of statistical modeling, the common assumption is that observations are normally distributed. In many real data applications, however, the true distribution is deviated from the normal. Thus, the main concern of most recent studies on analyzing data is to construct and the use of alternative distributions. In this regard, new classes of distributions such as slash and skew-sla...

On Mining Fuzzy Classification Rules for Imbalanced Data

Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...

On Mining Fuzzy Classification Rules for Imbalanced Data

Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...