Drift Severity Metric
نویسندگان
چکیده
Concept drift in data is usually considered only as abrupt or gradual thus referring to the speed of change. Such simple distinguishing by speed is sufficient for most of the problems, but there might be situations for which a finer representation would be of use. This paper studies further the phenomenon of concept drift and introduces a simple measure which is relevant to the speed and amount of change between different concepts.
منابع مشابه
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps
Mahalanobis distance metric takes feature weights and correlation into account in the distance computation, which can improve the performance of many similarity/dissimilarity based methods, such as kNN. Most existing distance metric learning methods obtain metric based on the raw features and side information but neglect the reliability of them. Noises or disturbances on instances will make cha...
متن کاملDrift correction for single-molecule imaging by molecular constraint field, a distance minimum metric
BACKGROUND The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecul...
متن کاملIs Familiality Associated with Downward Occupation Drift in Schizophrenia?
OBJECTIVE Downward occupational drift has been extensively investigated in schizophrenia. It is known that certain illness related factors, such as severity, affect drift, but the impact of familial factors has not been investigated. METHODS Occupation drift was studied among patients with schizophrenia/schizoaffective disorder (SZ/SZA)(n=523) and 130 affected sib pairs (ASPs). Drift was anal...
متن کاملCharacterizing Drifts for Proactive Drift Detection in Data Streams
The evolution of data such as changes in the underlying model known as concept drift present many challenges for data stream research. Currently most drift detection methods are able to locate the point of change, but are unable to provide meaningful information on the characteristics of change or utilize historical trends. In this thesis, we investigate two streams of research: (1) the magnitu...
متن کاملRanking with Distance Metric Learning for Biomedical Severity Detection
Estimating the severity of disease states or adverse-reactions to treatments is very important in drug and therapy development. We have developed a data-driven approach that uses the known severity of both negative controls (least severe) and positive controls (most severe) to define the range of possible severity and used this to learn a distance metric from data. This metric is used to measur...
متن کامل