Crowdsourcing: A Result Analysis

Models are generating from large data sets— and determining which subsets of data to mine— are becoming increasingly automated. What data to collect in the first place requires human intuition or experience, usually choose and supplied by a domain expert. In this paper a new approach is described to machine science which demonstrates for the first time that non-domain experts (crowd) can collectively formulate features, and provide values for those features and do the result analysis, which are based upon the result which will be output of this research. This was accomplished by building a web platform in which human groups should be interact to respond to questions likely from which  behavioral outcome will be  predict and pose new questions to their database if interested.

Here two web-based experiments have described, in the first site led to models that can predict users’ monthly electric energy consumption; the other led to models that can predict users’ body mass index. The values which are entered by user for Energy consumption and body mass index are used to analysis how the energy consumption can be reduced and how the body mass index should be maintained.