Vahida Attar

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Many real world data sets have an imbalanced distribution of the instances. Learning from such data sets results in the classifier being biased towards the majority class, thereby tending to misclassify the minority class samples. In this paper, we provide a technique, SkewBoost which classifies the minority instances correctly without compromising much on(More)
Agricultural research has been profited by technical advances such as automation, data mining. Today ,data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft wares are available, but data mining in agricultural soil datasets is a relatively a young research field. The large(More)
One of fundamental problem in the task of mining streaming data is the concept drift over time. Such data Streams may also exhibit high and varying degrees of class imbalance, which can further complicate the task. In scenarios like these, class imbalance is particularly difficult to overcome and has not been as thoroughly studied. Most of the studies on(More)
This paper proposes efficient method of embedding and extraction of data in Black and white pictures. The main focus of this method is on steganography in Black & white pictures. This method uses most of the flippable blocks without enforcing the odd-even features of non-uniform block. This improves the distortion in original image as blocks are(More)
Delay Tolerant Networking is the art and science of moving bits around in bad situations, such as between distant endpoints in deep space, or among unknown mobile users at uncertain positions. It is an opportunistic network where there is lack of end to end connectivity between source and destination, so that the communications take place using(More)