Using RRC Algorithm Classify the Proteins and Visualize in Biological Databases

Visualize biological database for protein is very complicated without Classify the protein properties.Protein classification is one of the major application of machine learning algorithms in the field of bio-informatics.The searching classification model works in two steps.Firstly, the correlation based feature selection for protein classification will be taken and strongly correlated features will be considered for classification using MST based . In second step, using Robust Regression, the classification will be performed. Based on results of RRC algorithm, it is highly has classification ratio than traditional machine learning algorithms such as SVM, Na�ve-bayes , Decision Trees

Forecasting audience increase on YouTube

User profiles constructed on Social Web platforms are often motivated by the need to maximise user reputation within a community. Subscriber, or follower, counts are an indicator of the influence and standing that the user has, where greater values indicate a greater perception or regard for what the user has to say or share. However, at present there lacks an understanding of the factors that lead to an increase in such audience levels, and how a user’s behaviour can a!ect their reputation. In this paper we attempt to fill this gap, by examining data collected from YouTube over regular time intervals. We explore the correlation between the subscriber counts and several behaviour features - extracted from both the user’s profile and the content they have shared. Through the use of a Multiple Linear Regression model we are able to forecast the audience levels that users will yield based on observed behaviour. Combining such a model with an exhaustive feature selection process, we yield statistically significant performance over a baseline model containing all features