---

Sri Ch.Madhu Babu

1.A Novel Enhanced Ensemble Clustering Techniques in Machine Learning and Data Mining

---

 Sajja Radharani, Amar Jukuntla, MadhuBabu Chevuru, P Amarnatha Reddy

Abstract

In recent years one of the most active research areas in data mining and machine learning is unsupervised learning. The objective of unsupervised learning is to model the essential structure or division in the facts in order to learn more about the data. In data mining clustering techniques very popular. DBSCAN is a type of partition grouping technique. The density-based clustering technique has played an essential role in the search for non-linear forms based on density. But, DBSCAN does not work well when dealing with groups of "variable density and high-dimensional data. It is sensitive to clustering parameters such as MinPts and Eps values. To overcome this we are using the OPTICA technique. The DBSCAN technique takes a long time for grouping formation. To improve this problem in OPTICS clustering algorithm.

 Volume 11 | Issue 5

2.Text Mining with Apache Hadoop over different Hadoop Clusters Architectures

E. Laxmi Lydia¹, Gorapalli Chandra Sekhar², Madhu BabuChevuru³, Dasari Ramya⁴, K. Vijaya Kumar⁵

Abstract: Big data is very much practical for real time applicational systems. One of the mostly used real time application worldwide are on unstructured documents. Large number of documents are managed and maintained through popular leading Big Data platform is Hadoop. It maintains all the information at Hadoop Distributed File System in Blocks. Irrespective of datasize, Big Data has opened its path to store and analyze the data which has consumed time. To overcome this, Hadoophas designed cluster process for large volumes of unstructured data computations. Three different cluster architectures like Standalone, Single node cluster and multi node clusters are considered. In this paper, Big Data allows Hadoop platform to boost the processing speed overlarge datasets through cluster architectures, which are studied and analyzed through text documents from newsgroup20 dataset. It identifies the challenges on text mining and its applications using Apache Hadoop.

3.  E Laxmi Lydia, N. Sharmili, T. V. Madhusudhanarao, Madhu Babu Chevuru and K. Vijaya Kumar, An Integrated Way for Teaching Hadoop & Big Data Analytics Course, International Journal of Recent Technology and Engineering, 8(2):1159-1163, July 2019, ISSN: 2277- 3878, DOI: 10.35940/ijrte.B1739.078219.