Dataset Validity Checker

Id of the actor whose datasets the validity checker is supposed to process.

Id of the task whose datasets the validity checker is supposed to process. Supersedes the actId.

Token of the user owning the examined actor/task. If not filled, token of the user starting the Dataset Validity Checker is used.

An email, where warnings about invalid datasets should be sent.

Set to true if you want the validity checker to discard all previously gathered information about datasets and start anew. You should use this option if you change the actor in a way that significantly changes its results, or if the website changes significantly in a way, that doesn't actually break your actor (e.g. the amount of different items available for purchase at an e-shop changes drastically).

A number of previous datasets that will be considered when determining whether the dataset is valid. If not filled, the value will be 100.

Minimal number of datasets processed needed to validate further datasets. Needs to be at most the same value as 'Previous Datasets Considered Count'. If not filled, the value will be 10.

Governs what attributes the Dataset Validity Checker considers to be numbers. If it is 'Strict', only values saved as number type will be considered as such. If 'Loose', strings that are numbers in a non-scientific notation are also handled like numbers. 'Strict' policy is generally better, but if you don't convert numbers to the proper type, using 'Loose' should give you better results.

Allows you to control, what will be the earliest run whose dataset will be processed by this run of Dataset Validity Checker. Will be superseded, if runs from later time have already been processed. Has to be ISO 8601 compliant date/time in UTC.

Allows you to control, what will be the latest run whose dataset will be processed by this run of Dataset Validity Checker. Has to be ISO 8601 compliant date/time in UTC.

Controls how different the dataset can be compared to the previously seen datasets to still be considered valid in terms of multiples of average difference. Default value is 5.

Controls how different the dataset can be compared to the previously seen datasets to still be considered valid in terms of multiples of maximal difference. Default value is 2.

Allows you to control both 'Maximal Multiplying Coefficient' and 'Average Multiplying Coefficient' at the same time. Is multiplicative, so a value of 2 increases both of them by a factor of 2. Default value is 1.