Medical record instances can have missing values which makes them unsuitable for
learning process. Data Imputation is normally done to fill one or more missing data attribute …

Distributed Denial of Service (DDoS) attacks in the cloud environment are not as simple as
the same attacks which occur in the traditional physical network environment. Not only one …

The paper is about the detection of unauthenticated news using Machine-learning methods
with different algorithms. There is lot of scope to check the reality of the news received from …

Classification is a supervised learning process which requires the decision labels available
for learning process. Decision classifier is a rule based approach for classification. This …

Imputation of missing data values is an important pre-processing task for mining of medical
data records. Application of data mining principles, techniques requires the dataset to be …

Discovering time profiled temporal patterns from time stamped transaction datasets is
addressed in our previous research works which includes proposing new support estimation …

An important observation which figures out when we look into several applications which are
the result of applying data science, machine learning, and deep learning techniques is that …

Finding temporal association patterns from temporal dataset is addressed in a wider
perspective in the existing literature. Discovering time profiled temporal patterns is …

Software component clustering is an unsupervised learning approach which is used to
cluster the software components. These clusters may then be used to study, analyze …

Software reuse is concerned about the possibility of reusability of software components. It is
important to think about ways, methods and approaches for extracting knowledge from …