%0 Journal Article %1 noauthororeditor %A Rabbani, Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam %D 2021 %J INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT %K & Analysis Bangladesh Bayes Bureau Classifier College Data Decision Discriminant Evaluation Extra Forest Instructors K Key Learning Linear Logistic Machine Mining Naive Neighbors Processing Random Regression School Statistics Teachers Technical Tree Trees factors of %N 1 %P 864-869 %T Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining %U https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan %V 6 %X According to the Bangladesh Bureau of Statistics BBS , the literacy rate in Bangladesh is increasing day by day. But, Its not acceptable to our present day. The role model of an education system is a teacher or instructor. Proper education can improve our literacy rate and also be a huge change for our future Digital Bangladesh. This enhancement is only possible to highly trained instructors or teachers. In order to improve an organizations training process, it’s important to assess how instructors are trained their students. This research has worked on identifying the key factors of training Technical School and College teachers in Bangladesh. The proposed work is conducted by Data Mining and Machine Learning. The methods of this experiment are Data Processing, Data Mining, and Analysis and Evaluation. Filtering our data is completed by using the Data Processing method. After that, the datasets are trained and tested by the Data Mining and Machine Learning tools. Finally, the experimental results are evaluated and analyzed by the different assessment tools. The accuracy of our trained models are 0.97 , 0.97 , 0.96 , 0.96 , 0.96 , 0.96 , 0.94 , 0.93 , 0.93 , 0.92 , 0.91 , 0.33 , 0.22 using the Logistic Regression, Extra Trees Classifier, Random Forest Classifier, Gradient Boosting Classifier, Light Gradient Boosting Machine, SVM Linear Kernel, Ada Boost Classifier, K Neighbors Classifier, Linear Discriminant Analysis, Decision Tree Classifier, Ridge Classifier, Quadratic Discriminant Analysis, Naive Bayes, respectively. As a result, the Logistic Regression does accurately identify and classify the key factors of training Technical School and College teachers. The Logistic Regression model accuracy is 0.97 which gives better accuracy than other machine learning algorithms. Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam Rabbani "Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47901.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan

@article{noauthororeditor, abstract = {According to the Bangladesh Bureau of Statistics BBS , the literacy rate in Bangladesh is increasing day by day. But, Its not acceptable to our present day. The role model of an education system is a teacher or instructor. Proper education can improve our literacy rate and also be a huge change for our future Digital Bangladesh. This enhancement is only possible to highly trained instructors or teachers. In order to improve an organizations training process, it’s important to assess how instructors are trained their students. This research has worked on identifying the key factors of training Technical School and College teachers in Bangladesh. The proposed work is conducted by Data Mining and Machine Learning. The methods of this experiment are Data Processing, Data Mining, and Analysis and Evaluation. Filtering our data is completed by using the Data Processing method. After that, the datasets are trained and tested by the Data Mining and Machine Learning tools. Finally, the experimental results are evaluated and analyzed by the different assessment tools. The accuracy of our trained models are 0.97 , 0.97 , 0.96 , 0.96 , 0.96 , 0.96 , 0.94 , 0.93 , 0.93 , 0.92 , 0.91 , 0.33 , 0.22 using the Logistic Regression, Extra Trees Classifier, Random Forest Classifier, Gradient Boosting Classifier, Light Gradient Boosting Machine, SVM Linear Kernel, Ada Boost Classifier, K Neighbors Classifier, Linear Discriminant Analysis, Decision Tree Classifier, Ridge Classifier, Quadratic Discriminant Analysis, Naive Bayes, respectively. As a result, the Logistic Regression does accurately identify and classify the key factors of training Technical School and College teachers. The Logistic Regression model accuracy is 0.97 which gives better accuracy than other machine learning algorithms. Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam Rabbani "Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47901.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan }, added-at = {2022-07-18T07:46:11.000+0200}, author = {Rabbani, Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam}, biburl = {https://www.bibsonomy.org/bibtex/28e47cf0a862138448e5e7ee53e661e1b/ijtsrd}, interhash = {76ed7322e3ab14a857e7f0263ccaf84c}, intrahash = {8e47cf0a862138448e5e7ee53e661e1b}, issn = {2456-6470}, journal = {INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT}, keywords = {& Analysis Bangladesh Bayes Bureau Classifier College Data Decision Discriminant Evaluation Extra Forest Instructors K Key Learning Linear Logistic Machine Mining Naive Neighbors Processing Random Regression School Statistics Teachers Technical Tree Trees factors of}, language = {English}, month = {December }, number = 1, pages = {864-869}, timestamp = {2022-07-18T07:46:11.000+0200}, title = {Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining }, url = {https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan}, volume = 6, year = 2021 }