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International Journal of Scientific & Technology Research

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IJSTR >> Volume 8 - Issue 8, August 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Literacy Rate Analysis Dashboard

[Full Text]

 

AUTHOR(S)

Kavita Sheoron

 

KEYWORDS

Indian literacy, literacy rate, data pre-processing, data analysis, machine learning

 

ABSTRACT

Education is the foremost important tool for change of the society and betterment of nation. Proficiency and level of training are fundamental pointers of the level of improvement accomplished by a general public. Spread of literacy is by and large connected with vital attributes of present day development for example, modernization, urbanization, trade and industrialization. Literacy shapes a vital contribution to generally improvement of society empowering them to understand their social, political and social condition better and react to it appropriately. Better education and literacy prompt a more noteworthy mindfulness and furthermore contributes in enhancement of economical and social conditions. Ministry of Human Resource Development (DISE) releases a data on literacy rate each year which can be exceptionally valuable in examining different elements influencing education rate of a state or an area. An all around structured dashboard that exhibits the best possible examination of the information will give a reasonable picture of proficiency in different locales of India. Data to be analyzed is handled and cleaned to draw out the most imperative and significant features. The data at that point analyzed gives the last outcome which is presented on dashboard making it easy to understand and comprehend.

 

REFERENCES

[1]. Isabelle Guyon,”An Introduction to Variable and Feature Selection” in Journal of Machine Learning Research 3 (2003) 1157-1182,2013.
[2]. Tarun Verma, “Literacy Rate Analysis” in International Journal of Scientific & Engineering Research Volume 3, Issue 7, July-2012.
[3]. JinsongLeng, “A Wrapper-Based Feature Selection for Analysis of Large Data Sets” in 3rd International Conference on Computer and Electrical Engineering (ICCEE 2010), 2010.
[4]. Aparna Samudra, “Trends and Factors affecting Female Literacy-An inter-district study of Maharashtra” in International Journal of Gender and Women’s Studies, June 2014.
[5]. The World Bank, “Education in India”, September 20, 2011.
[6]. EemeliLepp ̈aaho, “GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis” in Journal of Machine Learning Research 18 (2017) 1-5, April 2017.
[7]. 2001 Census Data, “Literacy and Level of Education” by Govt. of India.
[8]. Brijesh Kumar Baradwaj, “Mining Educational Data to Analyze Students‟ Performance” in (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, June, 2011.
[9]. Deepak Talwar, Dr.Meenu, “An Analysis of Literacy Rate In Haryana” in Journal of Business Management & Social Sciences Research (JBM&SSR) Volume 3, No.7, July 2014.
[10]. Navjeet Kaur, “Literacy Rate and Gender Gap in Scheduled Castes in India” in ICFAI National College, Patiala.
[11]. PradipChouhan, “A study on literacy and educational attainment of scheduled castes population in Maldah District of West Bengal, India” in Journal of Geography and Regional Planning Vol. 6(1), pp. 19-30, February, 2013
[12]. Jason Brownlee, “How to predict classification or regression outcomes with scikit-learn models in Python” (article).