Selecting the proper performance metric constitutes a key issue for most classification problems in the field of machine learning. Although the specialized literature has addressed several topics regarding these metrics, their symmetries have yet to be systematically studied. This research focuses on ten metrics based on a binary confusion matrix and their symmetric behaviour is formally defined under all types of transformations. Through simulated experiments, which cover the full range of datasets and classification results, the symmetric behaviour of these metrics is explored by exposing them to hundreds of simple or combined symmetric transformations. Cross-symmetries among the metrics and statistical symmetries are also explored. The results obtained show that, in all cases, three and only three types of symmetries arise: labelling inversion (between positive and negative classes); scoring inversion (concerning good and bad classifiers); and the combination of these two inversions. Additionally, certain metrics have been shown to be independent of the imbalance in the dataset and two cross-symmetries have been identified. The results regarding their symmetries reveal a deeper insight into the behaviour of various performance metrics and offer an indicator to properly interpret their values and a guide for their selection for certain specific applications.

In theaters and the filmmaking industry, video streams, images, audio streams and scalar data are commonly used. In these fields, one of the most important magnitudes to be collected and controlled is the light intensity in different scene spots. So, it is extremely important to be able to deploy a network of light sensors which are usually integrated in a more general Wireless Multimedia Sensor Network (WMSN). If many light measurements have to be acquired, the simpler and cheaper the sensor, the more affordable the WMSN will be. In this paper we propose the use of a set of very cheap light sensors (photodiodes) and to spectrally and directionally correct their measurements using mathematical methods. A real testing of the proposed solution has been accomplished, obtaining quite accurate light measurements. Testing results are also presented throughout the paper.

No abstract

No abstract

No abstract