A Comparative Study of RNN for Outlier Detection in Data Mining
نویسندگان
چکیده
We have proposed replicator neural networks (RNNs) for outlier detection [8]. Here we compare RNN for outlier detection with three other methods using both publicly available statistical datasets (generally small) and data mining datasets (generally much larger and generally real data). The smaller datasets provide insights into the relative strengths and weaknesses of RNNs. The larger datasets particularly test scalability and practicality of application.
منابع مشابه
Outlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis
Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient approach for detecting outliers in sensed data in a WSN. The outliers in sensed data can be ca...
متن کاملOutlier Detection on High Dimensional Data Using RNN
Background: Outlier detection is an important factor in data mining since it is used in various real time applications. Outlier is an extreme points that are not related to any of the class. Dealing with dimensions is the great challenge, due to “curse of dimensionality”, for effective outlier detection. In a high dimensional data space, it is difficult to detect most related points and most un...
متن کاملA comparative Study of Outlier Mining and Class Outlier Mining
Outliers can significantly affect data mining performance. Outlier mining is an important issue in knowledge discovery and data mining and has attracted increasing interests in recent years. Class outlier is promising research direction. Few researches have been done in this direction. The paper theme has two main goals: the first one is to show the significance of Class Outlier Mining by discu...
متن کاملOutlier Detection for Support Vector Machine using Minimum Covariance Determinant Estimator
The purpose of this paper is to identify the effective points on the performance of one of the important algorithm of data mining namely support vector machine. The final classification decision has been made based on the small portion of data called support vectors. So, existence of the atypical observations in the aforementioned points, will result in deviation from the correct decision. Thus...
متن کاملComparative Analysis of Outlier Detection Techniques
Data Mining simply refers to the extraction of very interesting patterns of the data from the massive data sets. Outlier detection is one of the important aspects of data mining which actually finds out the observations that are deviating from the common expected behavior. Outlier detection and analysis is sometimes known as outlier mining. In this paper, we have tried to provide the broad and ...
متن کامل