Detection of two Gaussian clusters
نویسندگان
چکیده
We discuss the detection of two Gaussian clusters given a cloud of points. The optimal learning curve for this unsupervised learning scenario is determined with a replica calculation. A comparison with principal component analysis and supervised learning allows to understand the three diierent learning phases observed.
منابع مشابه
BotOnus: an online unsupervised method for Botnet detection
Botnets are recognized as one of the most dangerous threats to the Internet infrastructure. They are used for malicious activities such as launching distributed denial of service attacks, sending spam, and leaking personal information. Existing botnet detection methods produce a number of good ideas, but they are far from complete yet, since most of them cannot detect botnets in an early stage ...
متن کاملA TWO-STAGE METHOD FOR DAMAGE DETECTION OF LARGE-SCALE STRUCTURES
A novel two-stage algorithm for detection of damages in large-scale structures under static loads is presented. The technique utilizes the vector of response change (VRC) and sensitivities of responses with respect to the elemental damage parameters (RSEs). It is shown that VRC approximately lies in the subspace spanned by RSEs corresponding to the damaged elements. The property is leveraged in...
متن کاملAdaptive Signal Detection in Auto-Regressive Interference with Gaussian Spectrum
A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...
متن کاملSemi-parametric Models Using False Positive Patterns for Face Detection
A good performance of a semi-parametric model has been demonstrated in many applications. That it can make flexible and compact model by controlling the number of clusters is the main advantage of it. However, it has many parameters to fit, and this feature makes learning more difficult. In this paper, we propose a new semi-parametric model. A proposed algorithm previously not defines the numbe...
متن کاملNegative Selection Based Data Classification with Flexible Boundaries
One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999