PAREEKSHA: a machine learning approach for intrusion and anomaly detection
A Nagaraja, S Aljawarneh - … of the First International Conference on Data …, 2018 - dl.acm.org
Membership functions help us to identify and know the similarity between two elements such
as vectors or sequences. The objective of this paper is to suggest a membership function …
as vectors or sequences. The objective of this paper is to suggest a membership function …
A machine learning approach for imputation and anomaly detection in IoT environment
R Vangipuram, RK Gunupudi, VK Puligadda… - Expert …, 2020 - Wiley Online Library
The problem of anomaly and attack detection in IoT environment is one of the prime
challenges in the domain of internet of things that requires an immediate concern. For …
challenges in the domain of internet of things that requires an immediate concern. For …
An efficient approach for imputation and classification of medical data values using class-based clustering of medical records
UR Yelipe, S Porika, M Golla - Computers & Electrical Engineering, 2018 - Elsevier
Medical data is usually not free from missing values and this is also true when data is
collected and sampled through various clinical trials. Existing Imputation techniques do not …
collected and sampled through various clinical trials. Existing Imputation techniques do not …
Mantra: a novel imputation measure for disease classification and prediction
S Aljawarneh, V Radhakrishna, GS Reddy - Proceedings of the first …, 2018 - dl.acm.org
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 …
learning process. Data Imputation is normally done to fill one or more missing data attribute …
A membership function for intrusion and anomaly detection of low frequency attacks
The ultimate objective of intrusion detection problem is to identify surprising intrusions that
compromise networks. Determining intrusions through the application of classifiers or …
compromise networks. Determining intrusions through the application of classifiers or …
An imputation measure for data imputation and disease classification of medical datasets
S Aljawarneh, V Radhakrishna… - AIP Conference …, 2019 - pubs.aip.org
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 …
data records. Application of data mining principles, techniques requires the dataset to be …
A similarity function for feature pattern clustering and high dimensional text document classification
Text document classification and clustering is an important learning task which fits to both
data mining and machine learning areas. The learning task throws several challenges when …
data mining and machine learning areas. The learning task throws several challenges when …
Similarity measures and text documents classfication accuracies using benchmark datasets
K Vinaykumar, S Rajavelu… - 2020 4th International …, 2020 - ieeexplore.ieee.org
The total amount of text data information available on the web has been remarkably
increasing the data accumulating and augmenting each day. Data and information that are …
increasing the data accumulating and augmenting each day. Data and information that are …
An efficient approach for dimensionality reduction and classification of high dimensional text documents
KV Kumar, R Srinivasan, EB Singh - … on Data Science, E-learning and …, 2018 - dl.acm.org
Feature representation and dimensionality reduction techniques are two important tasks in
text clustering and classification. In this paper, an approach for feature representation and …
text clustering and classification. In this paper, an approach for feature representation and …