Sony, commonly known as simply Sony (stylized in all caps), is a Japanese multinational conglomerate corporation headquartered in Minato, Tokyo, Japan. As a major technology company, it operates as one of the world's largest manufacturers of consumer and professional electronic products, the largest video game console company and the largest video game publisher. Through Sony Entertainment, it is one of the largest music companies (largest music publisher and second largest record label) and the third largest film studio, making it one of the most comprehensive media companies.
Sony MobileSony Mobile Communications Inc. (ソニーモバイルコミュニケーションズ株式会社) was a multinational telecommunications company founded on October 1, 2001, as a joint venture between Sony Corporation and Ericsson. It was originally incorporated as Sony Ericsson Mobile Communications, and headquartered in London, England, until Sony acquired Ericsson's share in the venture on February 16, 2012. On April 1, 2021, Sony integrated its electronics businesses including Sony Mobile into one company called Sony Corporation.
Loss functions for classificationIn machine learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of predictions in classification problems (problems of identifying which category a particular observation belongs to). Given as the space of all possible inputs (usually ), and as the set of labels (possible outputs), a typical goal of classification algorithms is to find a function which best predicts a label for a given input .
Support vector machineIn machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974).
Multiclass classificationIn machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into one of three or more classes (classifying instances into one of two classes is called binary classification). While many classification algorithms (notably multinomial logistic regression) naturally permit the use of more than two classes, some are by nature binary algorithms; these can, however, be turned into multinomial classifiers by a variety of strategies.
