Towards Improving Predictive Statistical Learning Model Accuracy by Enhancing Learning Technique

The accuracy of the statistical learning model depends on the learning technique used which in turn depends on the dataset’s values.In most research studies,the existence of missing values(MVs)is a vital problem.In addition,any dataset with MVs cannot be used for further analysis or with any data driven tool especially when the percentage of MVs are high.In this paper,the authors propose a novel algorithm for dealing with MVs depending on the feature selec-tion(FS)of similarity classifier with fuzzy entropy measure.The proposed algo-rithm imputes MVs in cumulative order.The candidate feature to be manipulated is selected using similarity classifier with Parkash’s fuzzy entropy measure.The predictive model to predict MVs within the candidate feature is the Bayesian Ridge Regression(BRR)technique.Furthermore,any imputed features will be incorporated within the BRR equation to impute the MVs in the next chosen incomplete feature.The proposed algorithm was compared against some practical state-of-the-art imputation methods by conducting an experiment on four medical datasets which were gathered from several databases repository with MVs gener-ated from the three missingness mechanisms.The evaluation metrics of mean abso-lute error(MAE),root mean square error(RMSE)and coefficient of determination(R2 score)were used to measure the performance.The results exhibited that perfor-mance vary depending on the size of the dataset,amount of MVs and the missing-ness mechanism type.Moreover,compared to other methods,the results showed that the proposed method gives better accuracy and less error in most cases.

Developing Image of Higher Education Performance

The study focused on Pattern Analysis Relationships between Basic Element Institutional Excellence in Education with a focus of the study: What is the actual profile of the basic elements of excellence of educational institutions, influence leadership, strategic planning, as well as students and focus stakeholders, focus staffs and faculty in order to develop the image Parahyangan University (UNPAR) performance by reference to the Performance Excellence Criteria for Education. The method used a qualitative approach and quantitative approach [1] with two models using qualitative-quantitative approaches, namely: two-phase design, dominant-les dominant design, and mixed methodology design. Respondents and the information in this study are a lecturer and head of the University.