The aim of the research is to find the best performance both of logistic regression and linear
discriminant which their threshold uses some various values. The performance tools used …

The paper aims to build and implement a predictive model called a fuzzy system. The fuzzy
rule bases component is generated by using the input-output data pairs. Its consequence …

The growth and development of children under five (toddlers) affect their health conditions.
Each region uniquely identifies the main factors influencing the toddler's health condition …

Binary choices, such as success or failure, acceptance or rejection, high or low, heavy or
light, and so on, can always be used to express decision-making. Based on the known …

The multiple regression model is very popular among researchers in both field of social and
science because it is easy to interpret and have a well-established theoretical framework …

Dengue fever is a disease that must be watched out and early preventive measures are
taken so the spread of this disease can be reduced. An early preventive dengue fever can …

The input of predictive models has an important role in directing the classification model to
have a satisfactory performance in predicting an unknown label of the instance class. The …

Abstract Learning Vector Quantization (LVQ) is a supervised learning algorithm commonly
used for statistical classification and pattern recognition. The competitive layer in LVQ …

Fraud detection is the first step to preventing fraud committed by both individuals and
organizations. The development of a high-performance classification model to detect fraud is …

Imbalanced classes can cause machine learning models to classify positive class instances
poorly, and the models require hyperparameter sets to optimal values. This study aims to …