Online labor service crowdsourcing analysis based on linear discriminant regression

In order to enhance the effectiveness of the research on the new-type business management of online labour service crowdsourcing effect based on sharing economy, this paper proposes an online labour service crowdsourcing effect analysis method based on linear discriminant regression. Firstly, it relies on knowledge service and business combination to promote the selection coordination of public users and crowdsourcing website in sharing value-driving and spacial technology, wherein, the value chain of crowdsourcing is the value network composed of infrastructure and operation process, it promotes the communication technology product or technical service through the product flow, service flow, information flow and capital flow of value network and establishes the research model; secondly, based on linear discriminant regression, it measures and tests the relationship between online labour service crowdsourcing effect and single class by aid of the nearest subspace classifier, based on the relationship between test effect and training effect obtained from the farthest subspace classifier, finally, it verifies the effectiveness of the algorithm through simulated experiment.