Browsing by Author "Pandey, Rajesh"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Causes of low achievement of students in mathematics(Department of Mathematics Educaion, 2023) Pandey, RajeshThis is a case study researchentitled “Causes of Low Achievement of Student in Mathematics”. The objective of this study was to identify the causes of low achievement of student in mathematics and to explore the way to improve student achievement in mathematics. This is qualitive research method base on case study. This study was bounded on Bag Devi Secondary School, Mulabari Bhumlu, Kavrepalanchok. This study was only related to the student in secondary level and also respondents of the study were mathematics teacher, five student and their parents. The respondent of the study was selected on the basis of purposive sampling method. Classroom observation, in-depth interview and document analysis were used as tool of data collection. This study found that lack of previous knowledge in subject matter, the learner does not have interest, learner does not have learning environment, student does not spend much time for learning mathematics, lack of teaching techniques, student have anxiety and exam fear, parents’ education is not good, lack of use teaching technology and family poor economic condition are the main causes of student difficulties to learn mathematics. The students have less motivation towards learning mathematics because the concerned bodies like their school, parents, teachers have given less concern for developing student friendly teaching and learning environment. To use student centered method, use teaching techniques for cooperative learning, teach mathematical problem in practical way, student spend necessary time for learning mathematics, to create learning environment in school and home are the main ways to improve student achievement in mathematics. This study is beneficial for secondary mathematics teacher, student and researcher.Item Hybrid Feature Selection and Feature Extraction Based Ensemble Method in Classification(Department of Computer Science and Information Technology, 2015) Pandey, RajeshEnsemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. The idea of ensemble learning is to employ multiple learners and combine their predictions. In this thesis, a novel method is proposed to build an ensemble of classifiers based on feature selection: Random selection, Relief and feature extraction: Principal component analysis method. The feature selection process chooses optimal subset of features according to objective function whereas feature extraction process maps the high dimensional dataset into lower dimensional dataset using the linear combination of original features. These feature selection and extraction method helps to produce diverse as well as accurate set of ensemble classifiers. A comparison of proposed method is made with the Bagging, AdaBoost, feature selection based NN, feature extraction based NN and also with plain NN using 22 benchmark dataset. The result obtained by the proposed method outperformed other algorithms with the following distribution: NN (14 cases), Random-NN (13 cases), Relief-NN (15 cases), PCANN (19 cases), AdaBoost (14 cases), Bagging (15 cases). Keywords: Ensemble methods, feature selection, feature extraction, Relief, Principal component analysis, AdaBoost, Bagging, NN, Random-NN, Relief-NN, PCA-NN