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a combining form of cross, used to indicate an interaction or exchange of two or more things (cross-addicted, cross-cultural, cross-pollination), the extension across a space or the covering of a distance (cross-border, crosscountry), or the passing across or perpendicular intersection with something (crossbar, crosscurrent).

Cross-Origin Resource Sharing (CORS) is an HTTP-header based mechanism that allows a server to indicate any origins (domain, scheme, or port) other than its own from which a browser should permit loading resources. CORS also relies on a mechanism by which browsers make a "preflight" request to the server hosting the cross-origin resource, in order to check that the server will permit the actual request. In that preflight, the browser sends headers that indicate the HTTP method and headers that will be used in the actual request.

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For security reasons, browsers restrict cross-origin HTTP requests initiated from scripts. For example, fetch() and XMLHttpRequest follow the same-origin policy. This means that a web application using those APIs can only request resources from the same origin the application was loaded from unless the response from other origins includes the right CORS headers.

The CORS mechanism supports secure cross-origin requests and data transfers between browsers and servers. Browsers use CORS in APIs such as fetch() or XMLHttpRequest to mitigate the risks of cross-origin HTTP requests.

The motivation is that the element from HTML 4.0 (which predates cross-site fetch() and XMLHttpRequest) can submit simple requests to any origin, so anyone writing a server must already be protecting against cross-site request forgery (CSRF). Under this assumption, the server doesn't have to opt-in (by responding to a preflight request) to receive any request that looks like a form submission, since the threat of CSRF is no worse than that of form submission. However, the server still must opt-in using Access-Control-Allow-Origin to share the response with the script.

This pattern of the Origin and Access-Control-Allow-Origin headers is the simplest use of the access control protocol. If the resource owners at wished to restrict access to the resource to requests only from (i.e., no domain other than can access the resource in a cross-origin manner), they would send:

Unlike simple requests, for "preflighted" requests the browser first sends an HTTP request using the OPTIONS method to the resource on the other origin, in order to determine if the actual request is safe to send. Such cross-origin requests are preflighted since they may have implications for user data.

The most interesting capability exposed by both fetch() or XMLHttpRequest and CORS is the ability to make "credentialed" requests that are aware of HTTP cookies and HTTP Authentication information. By default, in cross-origin fetch() or XMLHttpRequest calls, browsers will not send credentials.

This section lists headers that clients may use when issuing HTTP requests in order to make use of the cross-origin sharing feature. Note that these headers are set for you when making invocations to servers. Developers making cross-origin requests do not have to set any cross-origin sharing request headers programmatically.

Cross-Origin Resource Sharing (CORS) is an HTTP-header based mechanism that allows a server to indicate any origins (domain, scheme, or port) other than its own from which a browser should permit loading resources. CORS also relies on a mechanism by which browsers make a \"preflight\" request to the server hosting the cross-origin resource, in order to check that the server will permit the actual request. In that preflight, the browser sends headers that indicate the HTTP method and headers that will be used in the actual request.

Unlike simple requests, for \"preflighted\" requests the browser first sends an HTTP request using the OPTIONS method to the resource on the other origin, in order to determine if the actual request is safe to send. Such cross-origin requests are preflighted since they may have implications for user data.

The most interesting capability exposed by both fetch() or XMLHttpRequest and CORS is the ability to make \"credentialed\" requests that are aware of HTTP cookies and HTTP Authentication information. By default, in cross-origin fetch() or XMLHttpRequest calls, browsers will not send credentials.

that growing Internet connectivity and the digitisation of the global economy have resulted in the rapid increase in the collection, use, and transfer of data across borders, a trend that continues to accelerate;

that cross-border data flows increase living standards, create jobs, connect people in meaningful ways, facilitate vital research and development in support of public health, foster innovation and entrepreneurship, and allow for greater international engagement;

The performance measure reported by k-fold cross-validationis then the average of the values computed in the loop.This approach can be computationally expensive,but does not waste too much data(as is the case when fixing an arbitrary validation set),which is a major advantage in problems such as inverse inferencewhere the number of samples is very small.

See The scoring parameter: defining model evaluation rules for details.In the case of the Iris dataset, the samples are balanced across targetclasses hence the accuracy and the F1-score are almost equal.

The function cross_val_predict has a similar interface tocross_val_score, but returns, for each element in the input, theprediction that was obtained for that element when it was in the test set. Onlycross-validation strategies that assign all elements to a test set exactly oncecan be used (otherwise, an exception is raised).

The result of cross_val_predict may be different from thoseobtained using cross_val_score as the elements are grouped indifferent ways. The function cross_val_score takes an averageover cross-validation folds, whereas cross_val_predict simplyreturns the labels (or probabilities) from several distinct modelsundistinguished. Thus, cross_val_predict is not an appropriatemeasure of generalization error.

While i.i.d. data is a common assumption in machine learning theory, it rarelyholds in practice. If one knows that the samples have been generated using atime-dependent process, it is safer touse a time-series aware cross-validation scheme.Similarly, if we know that the generative process has a group structure(samples collected from different subjects, experiments, measurementdevices), it is safer to use group-wise cross-validation.

LeaveOneOut (or LOO) is a simple cross-validation. Each learningset is created by taking all the samples except one, the test set beingthe sample left out. Thus, for \(n\) samples, we have \(n\) differenttraining sets and \(n\) different tests set. This cross-validationprocedure does not waste much data as only one sample is removed from thetraining set:

Potential users of LOO for model selection should weigh a few known caveats.When compared with \(k\)-fold cross validation, one builds \(n\) modelsfrom \(n\) samples instead of \(k\) models, where \(n > k\).Moreover, each is trained on \(n - 1\) samples rather than\((k-1) n / k\). In both ways, assuming \(k\) is not too largeand \(k < n\), LOO is more computationally expensive than \(k\)-foldcross validation.

Each subject is in a different testing fold, and the same subject is never inboth testing and training. Notice that the folds do not have exactly the samesize due to the imbalance in the data. If class proportions must be balancedacross folds, StratifiedGroupKFold is a better option.

StratifiedGroupKFold is a cross-validation scheme that combines bothStratifiedKFold and GroupKFold. The idea is to try topreserve the distribution of classes in each split while keeping each groupwithin a single split. That might be useful when you have an unbalanceddataset so that using just GroupKFold might produce skewed splits.

The algorithm greedily assigns each group to one of n_splits test sets,choosing the test set that minimises the variance in class distributionacross test sets. Group assignment proceeds from groups with highest tolowest variance in class frequency, i.e. large groups peaked on one or fewclasses are assigned first. ff782bc1db